Xilin Xia
Xilin Xia
School of Architecture, Building and Civil Engineering, Loughborough University
Verified email at lboro.ac.uk - Homepage
Cited by
Cited by
An efficient and stable hydrodynamic model with novel source term discretisation schemes for overland flow and flood simulations
X Xia, Q Liang, X Ming, J Hou
Water Resources Research 53, 2017
A GPU-accelerated smoothed particle hydrodynamics (SPH) model for the shallow water equations
X Xia, Q Liang
Environmental Modelling & Software 75, 28-43, 2015
Balancing the source terms in a SPH model for solving the shallow water equations
X Xia, Q Liang, M Pastor, W Zou, YF Zhuang
Advances in water resources 59, 25-38, 2013
A full-scale fluvial flood modelling framework based on a high-performance integrated hydrodynamic modelling system (HiPIMS)
X Xia, Q Liang, X Ming
Advances in Water Resources 132, 103392, 2019
A new efficient implicit scheme for discretising the stiff friction terms in the shallow water equations
X Xia, Q Liang
Advances in water resources 117, 87-97, 2018
Efficient urban flood simulation using a GPU-accelerated SPH model
Q Liang, X Xia, J Hou
Environmental Earth Sciences, 2015
Catchment-scale high-resolution flash flood simulation using the GPU-based technology
Q Liang, X Xia, J Hou
Procedia Engineering 154, 975-981, 2016
A new depth-averaged model for flow-like landslides over complex terrains with curvatures and steep slopes
X Xia, Q Liang
Engineering Geology 234, 174-191, 2018
City-scale hydrodynamic modelling of urban flash floods: the issues of scale and resolution
Y Xing, Q Liang, G Wang, X Ming, X Xia
Natural Hazards 96 (1), 473-496, 2019
New prospects for computational hydraulics by leveraging high-performance heterogeneous computing techniques
Q Liang, L Smith, X Xia
Journal of Hydrodynamics 28 (6), 977-985, 2016
A novel 1D-2D coupled model for hydrodynamic simulation of flows in drainage networks
Q Li, Q Liang, X Xia
Advances in Water Resources 137, 103519, 2020
Recommendations for improving integration in national end-to-end flood forecasting systems: An overview of the FFIR (Flooding From Intense Rainfall) programme
DLA Flack, CJ Skinner, L Hawkness-Smith, G O’Donnell, RJ Thompson, ...
Water 11 (4), 725, 2019
Robust absorbing boundary conditions for shallow water flow models
J Hou, Q Liang, X Xia
Environmental Earth Sciences 74 (11), 7407-7422, 2015
Contradiction between the C‐property and mass conservation in adaptive grid based shallow flow models: cause and solution
Q Liang, J Hou, X Xia
International Journal for Numerical Methods in Fluids 78 (1), 17-36, 2015
Neurocomputing in surface water hydrology and hydraulics: a review of two decades retrospective, current status and future prospects
M Zounemat-Kermani, E Matta, A Cominola, X Xia, Q Zhang, Q Liang, ...
Journal of Hydrology, 125085, 2020
Real‐time flood forecasting based on a high‐performance 2D hydrodynamic model and numerical weather predictions
X Ming, Q Liang, X Xia, D Li, HJ Fowler
Water Resources Research, e2019WR025583, 2020
A deep convolutional neural network model for rapid prediction of fluvial flood inundation
S Kabir, S Patidar, X Xia, Q Liang, J Neal, G Pender
Journal of Hydrology 590, 125481, 2020
Simulation of hydraulic structures in 2D high-resolution urban flood modeling
Y Cui, Q Liang, G Wang, J Zhao, J Hu, Y Wang, X Xia
Water 11 (10), 2139, 2019
A deep convolutional neural network for rapid fluvial flood inundation modelling
S Kabir, S Patidar, X Xia, Q Liang, J Neal, G Pender
arXiv preprint arXiv:2006.11555, 2020
A multi-scale mapping approach based on a deep learning CNN model for reconstructing high-resolution urban DEMs
L Jiang, Y Hu, X Xia, Q Liang, A Soltoggio, SR Kabir
Water 12 (5), 1369, 2020
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