Articles | Volume 16, issue 3
https://doi.org/10.5194/gmd-16-977-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-977-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
08 Feb 2023
Model description paper |
| 08 Feb 2023
| 08 Feb 2023
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
Daniel Caviedes-Voullième
CORRESPONDING AUTHOR
Simulation and Data Lab Terrestrial Systems, Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany
Institute of Bio- and Geosciences: Agrosphere (IBG-3), Forschungszentrum Jülich, Germany
Mario Morales-Hernández
Fluid Mechanics, I3A, Universidad de Zaragoza, Zaragoza, Spain
Oak Ridge National Laboratory, Oak Ridge, USA
Matthew R. Norman
Oak Ridge National Laboratory, Oak Ridge, USA
Ilhan Özgen-Xian
Institute of Geoecology, Technische Universität Braunschweig, Braunschweig, Germany
Earth & Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, USA
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29 citations as recorded by crossref.
- Analyzing performance portability for a SYCL implementation of the 2D shallow water equations M. Büttner et al. 10.1007/s11227-025-07063-7
- Multi-scale hydraulic graph neural networks for flood modelling R. Bentivoglio et al. 10.5194/nhess-25-335-2025
- Effect of intense rainfall and high riverine water level on compound flood hazards in a river-valley city: A case study of Yingde, China L. Gao et al. 10.1016/j.jhydrol.2023.130044
- Single porosity model: Exploring the spatial resolution limits in complex urban patterns S. Nash et al. 10.1016/j.jhydrol.2024.131239
- Interpretable physics‐informed graph neural networks for flood forecasting M. Taghizadeh et al. 10.1111/mice.13484
- Application of 1D model for overland flow simulations on 2D complex domains Y. Zhang et al. 10.1016/j.advwatres.2024.104711
- Influence of building collapse on pluvial and fluvial flood inundation of metro stations in central Shanghai Z. Li et al. 10.5194/nhess-24-3977-2024
- Investigating optimal 2D hydrodynamic modeling of a recent flash flood in a steep Norwegian river using high-performance computing A. Moraru et al. 10.2166/hydro.2023.012
- Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data P. Costabile et al. 10.1029/2023WR034599
- Using integrated hydrological–hydraulic modelling and global data sources to analyse the February 2023 floods in the Umbeluzi Catchment (Mozambique) L. Cea et al. 10.5194/nhess-24-225-2024
- A novel multi-model ensemble framework for fluvial flood inundation mapping N. Mangukiya et al. 10.1016/j.envsoft.2024.106163
- Are 2D shallow-water solvers fast enough for early flood warning? A comparative assessment on the 2021 Ahr valley flood event S. Khosh Bin Ghomash et al. 10.5194/nhess-24-2857-2024
- An urban flood inundation model accelerated by the parallel acceleration technology W. Zhu et al. 10.1016/j.envsoft.2025.106441
- Technological Advances to Rescue Temporary and Ephemeral Wetlands: Reducing Their Vulnerability, Making Them Visible R. Jiménez-Melero et al. 10.3390/rs15143553
- Accelerating LASG/IAP climate system ocean model version 3 for performance portability using Kokkos J. Wei et al. 10.1016/j.future.2024.06.029
- Evaluation of 2D hydrodynamic-based rainfall/runoff modelling for soil erosion assessment at a seasonal scale P. Costabile et al. 10.1016/j.jhydrol.2024.130778
- GPU-parallelisation of Haar wavelet-based grid resolution adaptation for fast finite volume modelling: application to shallow water flows A. Chowdhury et al. 10.2166/hydro.2023.154
- Exploring the impact of urbanization on flood characteristics with the SCS-TRITON method H. Yu et al. 10.1007/s11069-023-06324-z
- Unravelling spatial heterogeneity of inundation pattern domains for 2D analysis of fluvial landscapes and drainage networks P. Costabile et al. 10.1016/j.jhydrol.2024.130728
- SERGHEI v2.0: introducing a performance-portable, high-performance, three-dimensional variably saturated subsurface flow solver (SERGHEI-RE) Z. Li et al. 10.5194/gmd-18-547-2025
- Multi-GPU parallelization of shallow water modelling on unstructured meshes B. Dong et al. 10.1016/j.jhydrol.2025.133105
- A GPU-accelerated and LTS-based 2D hydrodynamic model for the simulation of rainfall-runoff processes J. Wu et al. 10.1016/j.jhydrol.2023.129735
- High-performance computing in urban flood modeling: A study on spatial partitioning techniques and parallel performance T. Chen et al. 10.1016/j.jhydrol.2024.132474
- Nature-Based Solutions for Flood Mitigation and Soil Conservation in a Steep-Slope Olive-Orchard Catchment (Arquillos, SE Spain) P. Bohorquez et al. 10.3390/app13052882
- A complete methodology to assess hydraulic risk in small ungauged catchments based on HEC-RAS 2D Rain-On-Grid simulations W. Ennouini et al. 10.1007/s11069-024-06515-2
- Toward Brague river flood modelling 2: efforts to optimize HPC resources for a TELEMAC-2D code based on shallow water equations E. Ah-Woane et al. 10.1080/28375807.2025.2474241
- Nowcasting Floods in Detailed Scales Considering the Uncertainties Associated with impact-based Practical Applications V. Bellos et al. 10.1007/s11269-024-03988-5
- A high-order explicit Runge-Kutta approximation technique for the shallow water equations J. Guermond et al. 10.1016/j.compfluid.2024.106493
- A comparison of numerical schemes for the GPU-accelerated simulation of variably-saturated groundwater flow Z. Li et al. 10.1016/j.envsoft.2023.105900
Latest update: 14 May 2025
Short summary
This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such...
