OMI et al. (2026) A scalable physically based framework for large-scale GLOF simulation and downstream exposure assessment

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Environmental Research Letters
• Year: 2026
• Date: 2026-09-17
• Authors: Yutaro OMI, Orie Sasaki, Shinjiro Kanae
• DOI: 10.1088/1748-9326/aea91a

Research Groups

• Department of Geosciences, University of Colorado Boulder
• Institute of Hydrology and Meteorology, Royal Thimphu College

Short Summary

This study presents a scalable, physically based framework for simulating glacial lake outburst floods (GLOFs) and their downstream impacts across large spatial domains. The framework is applied to Bhutan, revealing strong basin-scale heterogeneity in flood impacts.

Objective

• Investigate the feasibility of a physically based framework for simulating GLOF-induced flood propagation and downstream exposure at large scales.

Study Configuration

• Spatial Scale: National scale (Bhutan)
• Temporal Scale: Long-term (hypothetical outburst scenario)

Methodology and Data

• Models used: A scalable, physically based framework combining lake dynamics, hydrology, and flood propagation models.
• Data sources: Satellite imagery, observation data, and reanalysis products.

Main Results

• The model reasonably reproduces observed GLOF impacts across Bhutan.
• Strong basin-scale heterogeneity in flood impacts is observed, with inundation depth and frequency varying widely among basins.
• Downstream propagation is strongly controlled by basin topography.
• Societal exposure is spatially decoupled from physical flood magnitude.

Contributions

• The study provides a scalable framework for large-scale GLOF risk assessments.
• It highlights the importance of considering lake magnitude, topography, and population distribution in assessing GLOF risk.

Funding

• This research was supported by the National Science Foundation (Award Number: 2021234) and the Royal Government of Bhutan's Department of Hydro-Met Services.

Citation

@article{OMI2026scalable,
  author = {OMI, Yutaro and Sasaki, Orie and Kanae, Shinjiro},
  title = {A scalable physically based framework for large-scale GLOF simulation and downstream exposure assessment},
  journal = {Environmental Research Letters},
  year = {2026},
  doi = {10.1088/1748-9326/aea91a},
  url = {https://doi.org/10.1088/1748-9326/aea91a}
}