Kajiyama et al. (2026) City boundaries for global urban water scarcity assessment

Identification

• Journal: Scientific Data
• Year: 2026
• Date: 2026-03-11
• Authors: Kiyoharu Kajiyama, Naota Hanasaki, Shinjiro Kanae
• DOI: 10.1038/s41597-026-06933-w

Research Groups

• School of Environment and Society, Institute of Science Tokyo, Tokyo, Japan
• Climate Change Impacts Assessment Section, Center for Climate Change Adaptation, National Institute for Environmental Studies, Ibaraki, Japan

Short Summary

This study introduces HydroUrbanMap (HUM), a global gridded dataset of hydrologically-informed city boundaries for 1,604 cities at 5 arcmin resolution, designed to improve urban water scarcity assessments by accurately delineating water-served populations and identifying accessible surface water sources. It demonstrates that HUM's approach overcomes limitations of existing urban delineation methods, providing a more realistic basis for city-specific water resource assessments.

Objective

• To develop a global gridded dataset of city boundaries (HydroUrbanMap - HUM) that incorporates hydrological attributes for improved urban water scarcity assessment, specifically by delineating city boundaries that include the population served by urban water services and estimating accessible surface water sources.

Study Configuration

• Spatial Scale: Global, 5 arcmin resolution.
• Temporal Scale: Base year 2010 for population data; mean annual streamflow calculated for 2010-2019.

Methodology and Data

• Models used: H08 global hydrological model.
• Data sources:
  • Gridded Population of the World (GPW) dataset (Version 4, Revision 11)
  • World Urbanization Prospects (WUP) (2018 Revision)
  • MERIT Hydro (high-resolution global hydrography map)
  • MERIT DEM (high-accuracy map of global terrain elevations)
  • W5E5v2 global meteorological dataset (input for H08)
  • City Water Map (for validation)
  • Global urban extent data by He et al. (for validation)

Main Results

• Developed HydroUrbanMap (HUM), a global gridded dataset of city boundaries for 1,604 cities at 5 arcmin resolution, including city masks, water inlets, outlets, and aqueduct origins.
• The estimated city populations in HUM's non-clustered city masks show strong agreement with WUP-reported populations (R² = 0.997, mean absolute error = 0.0418, or approximately 40,000 inhabitants per city).
• For clustered cities, the method effectively separated overlapping urban areas, with an R² of 0.937 and a mean absolute error of 0.324, retaining 83.6% of the initially reported population.
• HUM's city masks are generally larger than satellite-derived urban extent data (global median urban land cover rate of 0.7), capturing suburban and peri-urban zones.
• The Degree of Urbanization (DoU) method underestimated urban populations by approximately 326,490 inhabitants per city compared to HUM.
• Connectivity-based validation for city water inlets showed high agreement with documented facilities (mean PrecisionCWI = 0.808, mean RecallCWI = 0.851).
• Estimated aqueduct origins showed lower precision (mean PrecisionEAO = 0.303) and recall (mean RecallEAO = 0.396), consistent with their role in identifying both existing and potentially developable external water sources.
• 88% of the 245 validated cities had no false negatives for city water inlet estimation, demonstrating the robustness of the algorithm.
• 168 cities (10%) have multiple main rivers within their city masks, increasing to 1,089 cities (68%) when estimated aqueduct origins are considered.

Contributions

• Provides HydroUrbanMap (HUM), the first global gridded dataset of city boundaries specifically designed for urban water scarcity assessment, integrating hydrological attributes.
• Delineates city boundaries based on water-served populations, offering a more appropriate spatial extent for water resource assessment than existing methods based on fixed population density or built-up areas.
• Identifies city-specific river access points (inlets/outlets) and potential external water sources (aqueduct origins), addressing a critical data gap for global hydrological models.
• Enables city-specific water resource assessments worldwide, particularly valuable for cities lacking documented urban water service infrastructure.
• Offers a solution to overcome the overestimation of urban water scarcity in grid-based models and the limitations of basin-based or documented-facility-based approaches.

Funding

• Environment Research and Technology Development Fund (JPMEERF23S21120) of the Environmental Restoration and Conservation Agency provided by the Ministry of the Environment of Japan.
• JSPS KAKENHI Grant Numbers 21H05002, 23K26203, and 23KJ0C924.
• Ministry of Science and ICT through the National Research Foundation of Korea (RS-2025-02312954).
• InnoCORE program of the Ministry of Science and ICT (N10250155).

Citation

@article{Kajiyama2026City,
  author = {Kajiyama, Kiyoharu and Hanasaki, Naota and Kanae, Shinjiro},
  title = {City boundaries for global urban water scarcity assessment},
  journal = {Scientific Data},
  year = {2026},
  doi = {10.1038/s41597-026-06933-w},
  url = {https://doi.org/10.1038/s41597-026-06933-w}
}