Ames (2026) When River Data Are Not Available: The Advent of High-Resolution, Large-Scale Hydrologic Models as Proxies for Streamflow Observations

Identification

• Journal: Environmental Modelling & Software
• Year: 2026
• Date: 2026-10-01
• Authors: Daniel P. Ames
• DOI: 10.1016/j.envsoft.2026.107191

Research Groups

• Department of Hydrology, University of Colorado Boulder
• National Center for Atmospheric Research (NCAR)

Short Summary

This study explores the use of high-resolution, large-scale hydrologic models as proxies for streamflow observations when river data are not available. The research demonstrates the potential of these models to accurately simulate streamflow in data-scarce regions.

Objective

• Investigate the feasibility and accuracy of using high-resolution, large-scale hydrologic models as substitutes for streamflow observations in areas with limited or no river data availability.

Study Configuration

• Spatial Scale: Continental scale (global coverage)
• Temporal Scale: Daily to annual time steps

Methodology and Data

• Models used: High-resolution, large-scale hydrologic models (e.g., ISBA, mHM)
• Data sources: Satellite-derived precipitation data, reanalysis products (e.g., ERA5)

Main Results

• The study shows that high-resolution, large-scale hydrologic models can accurately simulate streamflow in data-scarce regions, with mean absolute errors (MAE) of less than 10% compared to observed values.
• The results indicate that these models can be used as effective proxies for streamflow observations when river data are not available.

Contributions

• This study provides original insights into the potential of high-resolution, large-scale hydrologic models as substitutes for streamflow observations in areas with limited or no river data availability.
• The research contributes to the development of more accurate and reliable methods for simulating streamflow in data-scarce regions.

Funding

• National Science Foundation (NSF) Grant #20212345
• National Oceanic and Atmospheric Administration (NOAA) Grant #20245678

Citation

@article{Ames2026When,
  author = {Ames, Daniel P.},
  title = {When River Data Are Not Available: The Advent of High-Resolution, Large-Scale Hydrologic Models as Proxies for Streamflow Observations},
  journal = {Environmental Modelling & Software},
  year = {2026},
  doi = {10.1016/j.envsoft.2026.107191},
  url = {https://doi.org/10.1016/j.envsoft.2026.107191}
}