ESSDD Earth System Science Data Discussions ESSDD Earth Syst. Sci. Data Discuss. 1866-3591 Göttingen, Germany 10.5194/essd-2026-402 MERIT-FullBasin: A global 90-meter basin dataset with a per-pixel upstream index and morphometric attributes Jiang Lulu https://orcid.org/0009-0004-1440-1603 1 2 3 4 Wu Huan 1 2 Chen Weitian 5 Huang Zhijun 3 4 Yang Ting 6 State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Hydrometeorological Disaster Mechanism and Warning of Ministry of Water Resources/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China Southern Marine Science and Engineering Laboratory (Zhuhai), and School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai 519082, China Future Water Laboratory, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing 314102, China CAS Engineering Laboratory for Yellow River Delta Modern Agriculture, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 03 08 2026 2026 1 49 Copyright: © 2026 Lulu Jiang et al. 2026 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://essd.copernicus.org/preprints/essd-2026-402/ The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-402/essd-2026-402.pdf

Fine-resolution hydrographic data are essential for flood prediction and risk mapping, large-sample hydrology, and machine-learning streamflow models. Yet no existing global product simultaneously provides basin identity, upstream-catchment topology, and morphometric attributes at per-pixel resolution. The 90 m MERIT-Hydro flow-direction and flow-accumulation rasters are the input, but computing per-pixel attributes from this 75-billion-pixel global grid exceeds the memory limits of standard geographic information system (GIS) software, and tile-based workflows fragment basins across boundaries. Here we present MERIT-FullBasin, a globally seamless dataset that delivers all three layers at per-pixel 90 m resolution. The first tier delineates 340,991 basins above 1 km&sup2; in upstream drainage area, together covering over 99.5 % of global land and partitioning the MERIT-Hydro land mask without gaps. The second tier provides a per-pixel depth-first search interval index (dfs_in, dfs_out); a single interval-containment comparison returns the complete upstream catchment of any target pixel, and the index losslessly encodes the underlying D8 flow-direction raster. The third tier delivers sixteen per-pixel upstream morphometric attribute rasters (eight terrain statistics and eight basin-shape metrics) at pixels with an upstream drainage area of at least 10 km&sup2;. The full pipeline completes in about 21 hours on a single 13-thread, terabyte-memory high-performance computing node. Each tier is verified independently: tier 1 by exact pixel-count match against the flow-accumulation reference, tier 2 by exact reconstruction of the D8 raster from the index alone, and tier 3 by perimeter benchmarking against three independent reference implementations. Products are distributed as GeoTIFFs co-registered with MERIT-Hydro together with per-basin attribute tables. Per-pixel queries reduce to a single GeoTIFF read or a single table lookup. Among published global hydrographic products, MERIT-FullBasin is the first dataset distributed as a per-pixel queryable flow-tree index. The dataset is openly available at <a href="https://doi.org/10.5281/zenodo.20344113" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.20344113</a> (Jiang et al., 2026).

 National Natural Science Foundation of China Grant 42275019 Grant 42088101 National Key Research and Development Program of China Grant 2024YFC3013302