García-Marquez et al. (2026) Environment90m – globally standardized environmental variables for freshwater science at high spatial resolution

Identification

• Journal: Earth system science data
• Year: 2026
• Date: 2026-02-27
• Authors: Jaime R. García-Marquez, Afroditi Grigoropoulou, Thomas Tomiczek, Marlene Schürz, Vanessa Bremerich, Yusdiel Torres‐Cambas, Merret Buurman, Kristi Bego, Giuseppe Amatulli, Sami Domisch
• DOI: 10.5194/essd-18-1541-2026

Research Groups

• Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Department of Community and Ecosystem Ecology, Berlin, Germany
• Freie Universität Berlin, Department of Biology, Chemistry, Pharmacy, Institute of Biology, Berlin, Germany
• Universität für Bodenkultur Wien, Institute of Hydrobiology and Aquatic Ecosystem Management, Vienna, Austria
• Yale University, School of the Environment, New Haven, CT, USA
• Spatial Ecology, Penn, Buckinghamshire, United Kingdom

Short Summary

This paper introduces Environment90m, a global, high-resolution dataset of 104 standardized environmental variables aggregated to 726 million freshwater sub-catchments, designed to support large-scale freshwater biodiversity research and conservation efforts.

Objective

• To provide a globally standardized, high-resolution environmental information baseline to characterize freshwater habitats anywhere in the world, addressing the challenge of establishing a global baseline for freshwater biodiversity.
• To facilitate globally standardized analyses and modeling workflows in spatial freshwater biodiversity science by aggregating environmental variables at a global scale and high spatial resolution based on the Hydrography90m stream network.

Study Configuration

• Spatial Scale: Global, with environmental variables aggregated to 726 million sub-catchments of the Hydrography90m dataset, corresponding to single stream segments at approximately 90 m spatial resolution.
• Temporal Scale: Varies by variable:
  • Climate: 1981–2010 (observation period), 2041–2070 and 2071–2100 (future projections).
  • Land Cover: Annual time-series from 1992–2020.
  • Streamflow: Long-term annual average for 1980–2010.
  • Aridity/Evapotranspiration: Long-term average for 1970–2000.
  • Hydrography, Soil, Elevation: Static (representing current state or long-term average).

Methodology and Data

• Models used:
  • GRASS GIS (Geographic Resources Analysis Support System)
  • GDAL/OGR (Geospatial Data Abstraction Library / OpenGIS Simple Features Reference Implementation)
  • AWK (pattern scanning and processing language)
  • hydrographr R-package for data download, processing, and integration.
• Data sources:
  • Hydrography90m (Amatulli et al., 2022): Global stream channel network and sub-catchment delineation (based on MERIT Hydro Digital Elevation Model at 90 m resolution).
  • CHELSA v2.1 (Karger et al., 2017, 2021): 19 bioclimatic variables at 1 km resolution (1981–2010 reference, future projections for 2041–2070 and 2071–2100 under SSPs 1.26, 3.70, 5.85 and GCMs UKESM1-0-LL, MPI-ESM1-2-HR, IPSL-CM6A-LR).
  • ESA Climate Change Initiative (CCI) Land Cover (ESA, 2017): 22 land cover categories at 300 m resolution (annual time-series from 1992–2020).
  • SoilGrids250 v2.0 (Hengl et al., 2017): 15 soil variables at 250 m resolution.
  • MERIT DEM (Yamazaki et al., 2017): Elevation at 90 m resolution.
  • FLO1K (Barbarossa et al., 2018): Modelled mean, maximum, and minimum annual streamflow at 1 km resolution (averaged for 1980–2010).
  • Global Aridity Index and Potential Evapotranspiration Climate Database v3 (Zomer and Trabucco, 2022): Aridity and potential evapotranspiration at 1 km resolution (1970–2000 average).

Main Results

• The Environment90m dataset was successfully generated, comprising 104 environmental variables aggregated to each of the 726 million sub-catchments of the Hydrography90m dataset.
• The dataset includes 45 variables related to topography and hydrography, 19 climate variables (for 1981–2010 and future projections for 2041–2070, 2071–2100 under various SSPs and GCMs), 22 land cover categories (annual time-series from 1992–2020), 15 soil variables, aridity, and modelled streamflow.
• For continuous variables, summary statistics (mean, minimum, maximum, range, standard deviation) are provided, while for categorical data, the proportion of each category is calculated within each sub-catchment.
• The dataset is openly available (4.1 terabytes in size) via https://hydrography.org/environment90m and the GeoFRESH online platform (https://geofresh.org/).
• The hydrographr R-package was extended with dedicated functions to facilitate efficient batch downloading, processing, and integration of Environment90m data with the Hydrography90m network, including new functionalities for processing upstream data of lakes.

Contributions

• Provides the first globally standardized environmental dataset at a high spatial resolution (approximately 90 m) specifically tailored for freshwater science, with variables aggregated to individual stream segments (sub-catchments), including previously neglected headwater streams.
• Addresses the significant computational challenges of processing large-scale, high-resolution geospatial data by offering the hydrographr R-package and the GeoFRESH online platform for efficient data access, integration, and custom workflow generation.
• Enables novel large-scale biogeographic analyses, species distribution modeling, and conservation planning in freshwater ecosystems by accounting for the dendritic network structure and aquatic-terrestrial linkages.
• Offers a comprehensive baseline of environmental information, including historical observations and future climate projections, which is crucial for assessing environmental changes and biodiversity loss in freshwater systems.

Funding

• Leibniz Competition project “Global freshwater biodiversity, biogeography and conservation” (grant no. J45/2018).
• German Research Foundation (NFDI4Earth, DFG project no. 460036893; NFDI4Biodiversity, DFG project no. 442032008; DFG reference number DO 1880/6-1, project no. 533943718).
• European Commission’s Horizon Europe Research and Innovation programme (grant nos. 101094434 (AquaINFRA), 101059264 (SOS-Water), 101093985 (DANUBE4all)).
• Alexander von Humboldt Foundation (Ref. 3.2-CUB-1212347-GF-P).
• DFG (CRC RESIST, SFB 1439/1345 2021–426547801).
• German Academic Exchange Service (DAAD reference no. 91902112).

Citation

@article{GarcíaMarquez2026Environment90m,
  author = {García-Marquez, Jaime R. and Grigoropoulou, Afroditi and Tomiczek, Thomas and Schürz, Marlene and Bremerich, Vanessa and Torres‐Cambas, Yusdiel and Buurman, Merret and Bego, Kristi and Amatulli, Giuseppe and Domisch, Sami},
  title = {Environment90m – globally standardized environmental variables for freshwater science at high spatial resolution},
  journal = {Earth system science data},
  year = {2026},
  doi = {10.5194/essd-18-1541-2026},
  url = {https://doi.org/10.5194/essd-18-1541-2026}
}