Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3577-2021
© Author(s) 2021. 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-14-3577-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
11 Jun 2021
Development and technical paper |
| 11 Jun 2021
| 11 Jun 2021
LISFLOOD-FP 8.0: the new discontinuous Galerkin shallow-water solver for multi-core CPUs and GPUs
Department of Civil and Structural Engineering, The University of Sheffield, Western Bank, Sheffield, UK
Georges Kesserwani
CORRESPONDING AUTHOR
Department of Civil and Structural Engineering, The University of Sheffield, Western Bank, Sheffield, UK
Jeffrey Neal
School of Geographical Sciences, University of Bristol, Bristol, UK
Paul Bates
School of Geographical Sciences, University of Bristol, Bristol, UK
Mohammad Kazem Sharifian
Department of Civil and Structural Engineering, The University of Sheffield, Western Bank, Sheffield, UK
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44 citations as recorded by crossref.
- An integrated approach to streamflow estimation and flood inundation mapping using VIC, RAPID and LISFLOOD-FP S. Nandi & M. Reddy 10.1016/j.jhydrol.2022.127842
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- An integrative modelling framework for predicting the compound flood hazards induced by tropical cyclones in an estuarine area H. Du et al. 10.1016/j.envsoft.2024.105996
- Locally Relevant High‐Resolution Hydrodynamic Modeling of River Floods at the Regional Scale A. Buttinger‐Kreuzhuber et al. 10.1029/2021WR030820
- Brief communication: Impact forecasting could substantially improve the emergency management of deadly floods: case study July 2021 floods in Germany H. Apel et al. 10.5194/nhess-22-3005-2022
- A new European coastal flood database for low–medium intensity events M. Le Gal et al. 10.5194/nhess-23-3585-2023
- LISFLOOD-FP 8.1: new GPU-accelerated solvers for faster fluvial/pluvial flood simulations M. Sharifian et al. 10.5194/gmd-16-2391-2023
- 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
- Unveiling the role of storm surges as a driver of flooding on the western Mediterranean: a case study of the Ebro Delta R. Romero-Martín et al. 10.1007/s11069-024-06984-5
- Bias in Flood Hazard Grid Aggregation S. Bryant et al. 10.1029/2023WR035100
- Enable high-resolution, real-time ensemble simulation and data assimilation of flood inundation using distributed GPU parallelization J. Wei et al. 10.1016/j.jhydrol.2023.129277
- Comparison of two modelling strategies for 2D large-scale flood simulations S. Dazzi et al. 10.1016/j.envsoft.2021.105225
- Sampling‐Based Methods for Uncertainty Propagation in Flood Modeling Under Multiple Uncertain Inputs: Finding Out the Most Efficient Choice M. Hajihassanpour et al. 10.1029/2022WR034011
- Evaluating the capability of UAV-Derived DEMs for flood hazard analysis H. Ozdemir & A. Akbas 10.1080/02723646.2025.2467912
- Hyper-resolution PCR-GLOBWB: opportunities and challenges from refining model spatial resolution to 1 km over the European continent J. Hoch et al. 10.5194/hess-27-1383-2023
- A new dataset of river flood hazard maps for Europe and the Mediterranean Basin F. Dottori et al. 10.5194/essd-14-1549-2022
- Integrating Connectivity Into Hydrodynamic Models: An Automated Open‐Source Method to Refine an Unstructured Mesh Using Remote Sensing K. Wright et al. 10.1029/2022MS003025
- The quantitative assessment of impact of pumping capacity and LID on urban flood susceptibility based on machine learning Y. Wu et al. 10.1016/j.jhydrol.2023.129116
- Enhancing transparency in data-driven urban pluvial flood prediction using an explainable CNN model W. Gao et al. 10.1016/j.jhydrol.2024.132228
- 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
- Influence of model configuration for coastal flooding across Europe M. Le Gal et al. 10.1016/j.coastaleng.2024.104541
- Fast simulation and prediction of urban pluvial floods using a deep convolutional neural network model Y. Liao et al. 10.1016/j.jhydrol.2023.129945
- Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS) M. Wilson & T. Coulthard 10.5194/gmd-16-2415-2023
- Can atmospheric reanalysis datasets reproduce flood inundation at regional scales? A systematic analysis with ERA5 over Mahanadi River Basin, India H. Singh & M. Mohanty 10.1007/s10661-023-11798-2
- Multi-GPU parallelization of shallow water modelling on unstructured meshes B. Dong et al. 10.1016/j.jhydrol.2025.133105
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- A novel multi-scenario mitigation model for rainstorm flood disasters L. Wen et al. 10.1016/j.ijdrr.2025.105321
- Accelerating flash flood simulations: An efficient GPU implementation for a slim shallow water solver A. Rak et al. 10.1016/j.envsoft.2024.106030
- 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
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- Flood Hazard Mapping with Distributed Hydrological Simulations and Remote-Sensed Slackwater Sediments in Ungauged Basins J. del Moral-Erencia et al. 10.3390/w13233434
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- A review of recent advances in urban flood research C. Agonafir et al. 10.1016/j.wasec.2023.100141
- Technical Note: Resolution enhancement of flood inundation grids S. Bryant et al. 10.5194/hess-28-575-2024
- Recent Advances and New Frontiers in Riverine and Coastal Flood Modeling K. Jafarzadegan et al. 10.1029/2022RG000788
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Latest update: 01 Apr 2025
Short summary
LISFLOOD-FP has been extended with new shallow-water solvers – DG2 and FV1 – for modelling all types of slow- or fast-moving waves over any smooth or rough surface. Using GPU parallelisation, FV1 is faster than the simpler ACC solver on grids with millions of elements. The DG2 solver is notably effective on coarse grids where river channels are hard to capture, improving predicted river levels and flood water depths. This marks a new step towards real-world DG2 flood inundation modelling.
LISFLOOD-FP has been extended with new shallow-water solvers – DG2 and FV1 – for modelling all...
