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GMesh: A Flexible Voronoi-Based Mesh Generator with Local Refinement for Watershed Hydrological Modeling.

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Název: GMesh: A Flexible Voronoi-Based Mesh Generator with Local Refinement for Watershed Hydrological Modeling.
Autoři: Velásquez, Nicolás, Díaz, Miguel, Arenas, Antonio
Zdroj: Hydrology (2306-5338); Oct2025, Vol. 12 Issue 10, p255, 19p
Témata: HYDROLOGIC models, WATERSHEDS, VORONOI polygons, DIGITAL elevation models, NUMERICAL grid generation (Numerical analysis), OPEN source software
Abstrakt: Partial Differential Equation (PDE)-based hydrologic models demand extensive preprocessing, creating a bottleneck and slowing down the model setup process. Mesh generation typically lacks integration with hydrological features like river networks. We present GHOST Mesh (GMesh), an automated, watershed-oriented mesh generator built within the Watershed Modeling Framework (WMF), to address this. While primarily designed for the GHOST hydrological model, GMesh's functionalities can be adapted for other models. GMesh enables rapid mesh generation in Python by incorporating Digital Elevation Models (DEMs), flow direction maps, network topology, and online services. The software creates Voronoi polygons that maintain connectivity between river segments and surrounding hillslopes, ensuring accurate surface–subsurface interaction representation. Key features include customizable mesh generation and variable refinement to target specific watershed areas. We applied GMesh to Iowa's Bear Creek watershed, generating meshes from 10,000 to 30,000 elements and analyzing their effects on simulated stream flows. Results show that higher mesh resolutions enhance peak flow predictions and reduce response time discrepancies, while local refinements improve model performance with minimal additional computation. GMesh's open-source nature streamlines mesh generation, offering researchers an efficient solution for hydrological analysis and model configuration testing. [ABSTRACT FROM AUTHOR]
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Abstrakt:Partial Differential Equation (PDE)-based hydrologic models demand extensive preprocessing, creating a bottleneck and slowing down the model setup process. Mesh generation typically lacks integration with hydrological features like river networks. We present GHOST Mesh (GMesh), an automated, watershed-oriented mesh generator built within the Watershed Modeling Framework (WMF), to address this. While primarily designed for the GHOST hydrological model, GMesh's functionalities can be adapted for other models. GMesh enables rapid mesh generation in Python by incorporating Digital Elevation Models (DEMs), flow direction maps, network topology, and online services. The software creates Voronoi polygons that maintain connectivity between river segments and surrounding hillslopes, ensuring accurate surface–subsurface interaction representation. Key features include customizable mesh generation and variable refinement to target specific watershed areas. We applied GMesh to Iowa's Bear Creek watershed, generating meshes from 10,000 to 30,000 elements and analyzing their effects on simulated stream flows. Results show that higher mesh resolutions enhance peak flow predictions and reduce response time discrepancies, while local refinements improve model performance with minimal additional computation. GMesh's open-source nature streamlines mesh generation, offering researchers an efficient solution for hydrological analysis and model configuration testing. [ABSTRACT FROM AUTHOR]
ISSN:23065338
DOI:10.3390/hydrology12100255