Liao et al. (2026) An Unstructured Voronoi Mesh Framework for Large‐Scale Hydrologic and Land Surface Models

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

Identification

• Journal: Journal of Advances in Modeling Earth Systems
• Year: 2026
• Date: 2026-11-01
• Authors: Chang Liao, Darren Engwirda, Donghui Xu, Tian Zhou, Zeli Tan, Lai-Yung Ruby Leung
• DOI: 10.1029/2025ms005442

Research Groups

Not specified in the abstract.

Short Summary

This study introduces a novel framework for generating Hydrologic Refined Meshes (HRMs) that seamlessly integrates crucial land surface features like river networks and watershed boundaries into the mesh generation process. The resulting variable-resolution (4–50 km) Voronoi meshes accurately capture land surface heterogeneity, effectively representing key landscape features and river networks with significantly fewer computational cells.

Objective

• To develop and implement a novel framework for generating Hydrologic Refined Meshes (HRMs) that strategically refines meshes based on crucial land surface features (river networks, watershed boundaries, lake boundaries) to improve the performance of continental-to-global hydrologic and land surface models.

Study Configuration

• Spatial Scale: Continental-to-global scale, with variable mesh resolution ranging from 4 km to 50 km.
• Temporal Scale: Not specified in the abstract.

Methodology and Data

• Models used: Model for Prediction Across Scales (MPAS) architecture, leveraging Centroidal Voronoi Tessellations properties and dual-grid topology.
• Data sources: Not explicitly stated, but implied to include topographic (surface elevation) and hydrographic (river networks, watershed boundaries, lake boundaries) datasets for mesh generation and evaluation.

Main Results

• The HRM framework provides a generalized, feature-driven workflow for strategic mesh refinement.
• The generated variable-resolution (4–50 km) Voronoi mesh accurately captures land surface features, including river networks, watershed boundaries, and lake boundaries.
• The mesh effectively captures surface elevation, resolving most key landscape features despite using nearly half the cell count compared to traditional approaches.
• River networks are accurately represented by high-resolution cells aligned along their courses.
• The conceptual river network generated by the mesh deviates by only approximately 1 km on average from the true river network.

Contributions

• Introduction of a novel, generalized, and feature-driven framework for generating Hydrologic Refined Meshes (HRMs) that strategically refines computational meshes.
• Seamless integration of critical land surface features (river networks, watershed boundaries, lake boundaries) directly into the mesh generation process.
• Demonstration of improved representation of land surface heterogeneity and key landscape features using variable-resolution meshes, while significantly reducing the number of computational cells.

Funding

Not specified in the abstract.

Citation

@article{Liao2026Unstructured,
  author = {Liao, Chang and Engwirda, Darren and Xu, Donghui and Zhou, Tian and Tan, Zeli and Leung, Lai-Yung Ruby},
  title = {An Unstructured Voronoi Mesh Framework for Large‐Scale Hydrologic and Land Surface Models},
  journal = {Journal of Advances in Modeling Earth Systems},
  year = {2026},
  doi = {10.1029/2025ms005442},
  url = {https://doi.org/10.1029/2025ms005442}
}