Innovations towards the next generation of shallow flow models

Özgen‐Xian, Ilhan; Xia, Xilin; Liang, Qiuhua; Hinkelmann, Reinhard; Liang, Dongfang; Hou, Jingming

doi:10.1016/j.advwatres.2021.103867

Cited by 3 publications

(1 citation statement)

References 17 publications

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“…SERGHEI-SWE enables the simulation of surface hydrodynamics of overland flow and streamflow seamlessly and across scales. Historically, hydrological models featuring surface flow have relied on kinematic or zero-inertia (diffusive) approximations due to their apparent simplicity (Caviedes- Kollet et al, 2017) and because until the last decade, robust SWE solvers were not available (Caviedes- Voullième et al, 2020a;García-Navarro et al, 2019;Simons et al, 2014;Özgen-Xian et al, 2021). However, the current capabilities of SWE solvers, the increase in computational capabilities, and the need to better exploit parallelism -easier to achieve with explicit solvers than with implicit solvers, as usually required by diffusive equations (Caviedes- -have been pushing to replace simplified surface flow models (for hydrological purposes) with fully dynamic SWE solvers.…”

Section: Introductionmentioning

confidence: 99%

SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics

et al. 2023

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Abstract. The Simulation EnviRonment for Geomorphology, Hydrodynamics, and Ecohydrology in Integrated form (SERGHEI) is a multi-dimensional, multi-domain, and multi-physics model framework for environmental and landscape simulation, designed with an outlook towards Earth system modelling. At the core of SERGHEI's innovation is its performance-portable high-performance parallel-computing (HPC) implementation, built from scratch on the Kokkos portability layer, allowing SERGHEI to be deployed, in a performance-portable fashion, in graphics processing unit (GPU)-based heterogeneous systems. In this work, we explore combinations of MPI and Kokkos using OpenMP and CUDA backends. In this contribution, we introduce the SERGHEI model framework and present with detail its first operational module for solving shallow-water equations (SERGHEI-SWE) and its HPC implementation. This module is designed to be applicable to hydrological and environmental problems including flooding and runoff generation, with an outlook towards Earth system modelling. Its applicability is demonstrated by testing several well-known benchmarks and large-scale problems, for which SERGHEI-SWE achieves excellent results for the different types of shallow-water problems. Finally, SERGHEI-SWE scalability and performance portability is demonstrated and evaluated on several TOP500 HPC systems, with very good scaling in the range of over 20 000 CPUs and up to 256 state-of-the art GPUs.

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Section: Introductionmentioning

confidence: 99%

SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics

et al. 2023

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A comparison of numerical schemes for the GPU-accelerated simulation of variably-saturated groundwater flow

Li,

Caviedes-Voullième,

Özgen-Xian

et al. 2024

Environmental Modelling & Software

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Shallow-Flow Velocity Predictions Using Discontinuous Galerkin Solutions

et al. 2023

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Numerical solvers of the two-dimensional (2D) shallow water equations (2D-SWE) can be an efficient option to predict spatial distribution of velocity fields in quasi-steady flows past or throughout hydraulic engineering structures. A second-order finite volume solver (FV2) spuriously elongates small-scale recirculating eddies within its predictions, unless sustained by an artificial eddy viscosity, while a third-order finite volume (FV3) solver can distort the eddies within its predictions. The extra complexity in a second-order discontinuous Galerkin (DG2) solver leads to significantly reduced error dissipation and improved predictions at a coarser resolution, making it a viable contender to acquire velocity predictions in shallow flows. This paper analyses this predictive capability for a grid-based, open source DG2 solver with reference to FV2 or FV3 solvers for simulating velocity magnitude and direction at the sub-meter scale. The simulated predictions are assessed against measured velocity data for four experimental test cases. The results consistently indicate that the DG2 solver is a competitive choice to efficiently produce more accurate velocity distributions for the simulations dominated by smooth flow regions. Practical ApplicationsThe estimation of the spatial distribution of horizontal velocity fields is useful to analyse the design of hydraulic and flood-defence structures undergoing shallow water flow processes. Examples include flooding through a residential area with piered buildings where recirculation flow eddies occur within side cavities, past building blocks, and across of street junctions. This paper demonstrates the utility of a relatively new hydraulic simulation tool, so-called DG2 solver, as an alternative to existing finite volume solvers featured in popular tools such as HEC-RAS 2D, Rubar20, Iber and TUFLOW-HPC. The DG2 solver is open source, as part of the LISFLOOD-FP 8.0 software suite, and particularly excels in the estimation of velocity fields that are more informative of the flow processes within a few minutes of simulation time. The proposed simulation tool is limited to modelling problems where the depth-integrated assumption of the shallow water equations is appropriate.

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Innovations towards the next generation of shallow flow models

Cited by 3 publications

References 17 publications

SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics

SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics

A comparison of numerical schemes for the GPU-accelerated simulation of variably-saturated groundwater flow

Shallow-Flow Velocity Predictions Using Discontinuous Galerkin Solutions

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