Journal Articles

Yang, H, Cui, X, Cai, Y, Wu, Z, Gao, S, Yu, B, Wang, Y, Li, K, Duan, Z, Liang, Q (2024) Coupling Downscaling and Calibrating Methods for Generating High-Quality Precipitation Data with Multisource Satellite Data in the Yellow River Basin, Remote Sensing, 16(8), pp.1318-1318, DOI: 10.3390/rs16081318.

Wang, H, Wang, G, Fu, R, Zheng, J, Wang, P, Yu, F, Liang, Q (2024) Graphics processing unit (GPU)-enhanced nonhydrostatic model with grid nesting for global tsunami propagation and coastal inundation, Physics of Fluids, 36(4), ISSN: 1070-6631. DOI: 10.1063/5.0203639.

Xia, X, Jarsve, KT, Dijkstra, T, Liang, Q, Meng, X, Chen, G (2023) An integrated hydrodynamic model for runoff-generated debris flows with novel formulation of bed erosion and deposition, Engineering Geology, 326, 107310, ISSN: 0013-7952. DOI: 10.1016/j.enggeo.2023.107310.

Wang, H, Wang, G, Zheng, J, Liang, Q, Tao, A (2023) Advancements in nearshore wave modeling: A unified one-layer nonhydrostatic approach, Physics of Fluids, 35(7), ISSN: 1070-6631. DOI: 10.1063/5.0159266.

Tong, X, Lai, X, Liang, Q (2023) An improved non-point source pollution model for catchment-scale hydrological processes and phosphorus loads, Journal of Hydrology, 621, pp.129588-129588, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2023.129588.

Hill, B, Liang, Q, Bosher, L, Chen, H, Nicholson, A (2023) A systematic review of natural flood management modelling: approaches, limitations, and potential solutions, Journal of Flood Risk Management, 16(3), e12899, ISSN: 1753-318X. DOI: 10.1111/jfr3.12899.

Cui, Y, Liang, Q, Xiong, Y, Wang, G, Wang, T, Chen, H (2023) Assessment of Object-Level Flood Impact in an Urbanized Area Considering Operation of Hydraulic Structures, Sustainability, 15(5), pp.4589-4589, DOI: 10.3390/su15054589.

Zhong, B, Wang, Z, Yang, H, Xu, H, Gao, M, Liang, Q (2022) Parameter optimization of SWMM model using integrated Morris and GLUE methods, Water, 15(1), 149, DOI: 10.3390/w15010149.

Guan, X, Xia, C, Xu, H, Liang, Q, Ma, C, Xu, S (2022) Flood risk analysis integrating of Bayesian-based time-varying model and expected annual damage considering non-stationarity and uncertainty in the coastal city, Journal of Hydrology, 617(Part B), 129038, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2022.129038.

Lin, L, Tang, C, Liang, Q, Wu, Z, Wang, X, Zhao, S (2022) Rapid urban flood risk mapping for data-scarce environments using social sensing and region-stable deep neural network, Journal of Hydrology, 617(Part A), 128758, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2022.128758.

Xiong, Y, Liang, Q, Zheng, J, Stolle, J, Nistor, I, Wang, G (2022) A fully coupled hydrodynamic-DEM model for simulating debris dynamics and impact forces, Ocean Engineering, 255, 111468, ISSN: 0029-8018. DOI: 10.1016/j.oceaneng.2022.111468.

Su, X, Liang, Q, Xia, X (2022) A new GPU-accelerated coupled discrete element and depth-averaged model for simulation of flow-like landslides, Environmental Modelling & Software, 153, 105412, ISSN: 1364-8152. DOI: 10.1016/j.envsoft.2022.105412.

Ma, Y, Xia, X, Liang, Q, Wan, H (2022) Investigating the Impact of Spatial Distribution of Sustainable Drainage System (SuDS) Components on Their Flood Mitigation Performance in Communities with High Groundwater Levels, Water, 14(9), pp.1367-1367, DOI: 10.3390/w14091367.

Zhao, J and Liang, Q (2022) Novel variable reconstruction and friction term discretisation schemes for hydrodynamic modelling of overland flow and surface water flooding, Advances in Water Resources, 163, 104187, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2022.104187.

Xing, Y, Chen, H, Liang, Q, Ma, X (2022) Improving the performance of city-scale hydrodynamic flood modelling through a GIS-based DEM correction method, Natural Hazards, 112(3), pp.2313-2335, ISSN: 0921-030X. DOI: 10.1007/s11069-022-05267-1.

Ming, X, Liang, Q, Dawson, R, Xia, X, Hou, J (2022) A quantitative multi-hazard risk assessment framework for compound flooding considering hazard inter-dependencies and interactions, Journal of Hydrology, 607, 127477, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2022.127477.

Zhou, X, Moinuddin, M, Renaud, F, Barrett, B, Xu, J, Liang, Q, Zhao, J, Xia, X, Bosher, L, Huang, S, Hoey, T (2022) Development of an SDG interlinkages analysis model at the river basin scale: a case study in the Luanhe River Basin, China, Sustainability Science, 17(4), pp.1405-1433, ISSN: 1862-4065. DOI: 10.1007/s11625-021-01065-z.

Xing, Y, Shao, D, Liang, Q, Chen, H, Ma, X, Ullah, I (2021) Investigation of the drainage loss effects with a street view based drainage calculation method in hydrodynamic modelling of pluvial floods in urbanized area, Journal of Hydrology, 605, 127365, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2021.127365.

Liu, K, Ke, L, Wang, J, Jiang, L, Richards, KS, Sheng, Y, Zhu, Y, Fan, C, Zhan, P, Luo, S, Cheng, J, Chen, T, Ma, R, Liang, Q, Madson, A, Song, C (2021) Ongoing drainage reorganization driven by rapid lake growths on the Tibetan Plateau, Geophysical Research Letters, 48(24), e2021GL095795, ISSN: 0094-8276. DOI: 10.1029/2021GL095795.

Nian, T, Li, D, Liang, Q, Wu, H, Guo, X (Accepted for publication) Multi-phase flow simulation of landslide dam formation process based on extended coupled DEM-CFD method, Computers and Geotechnics, 140, ISSN: 0266-352X. DOI: 10.1016/j.compgeo.2021.104438.

Su, X, Xia, X, Liang, Q, Hou, J (2021) A coupled discrete element and depth-averaged model for dynamic simulation of flow-like landslides, Computers and Geotechnics, 141, 104537, ISSN: 0266-352X. DOI: 10.1016/j.compgeo.2021.104537.

Chen, H, Zhao, J, Liang, Q, Maharjan, SB, Joshi, SP (2021) Assessing the potential impact of glacial lake outburst floods on individual objects using a high-performance hydrodynamic model and open-source data, Science of the Total Environment, 806(Part 3), 151289, ISSN: 0048-9697. DOI: 10.1016/j.scitotenv.2021.151289.

Hou, J-M, Shi, B-S, Liang, Q, Tong, Y, Kang, Y-D, Zhang, Z-A, Bai, G-G, Gao, X-J, Yang, X (2021) A graphics processing unit-based robust numerical model for solute transport driven by torrential flow condition, Journal of Zhejiang University Science A, 22(10), pp.835-850, ISSN: 1673-565X. DOI: 10.1631/jzus.A2000585.

Zhao, J, Chen, H, Liang, Q, Xia, X, Xu, J, Hoey, T, Barrett, B, Renaud, FG, Bosher, L, Zhou, X (2021) Large-scale flood risk assessment under different development strategies: the Luanhe River Basin in China, Sustainability Science, 17(4), pp.1365-1384, ISSN: 1862-4065. DOI: 10.1007/s11625-021-01034-6.

Zhao, W, Xia, X, Su, X, Liang, Q, Liu, X, Ju, N (2021) Movement process analysis of the high-speed long-runout Shuicheng landslide over 3-D complex terrain using a depth-averaged numerical model, Landslides, 18(9), pp.3213-3226, ISSN: 1612-510X. DOI: 10.1007/s10346-021-01695-5.

Han, H, Hou, J, Bai, G, Li, B, Wang, T, Li, X, Gong, J, Gao, X, Su, F, Wang, Z, Liang, Q (2021) A deep learning technique-based automatic monitoring method for experimental urban road inundation, Journal of Hydroinformatics, 23(4), pp.764-781, ISSN: 1464-7141. DOI: 10.2166/hydro.2021.156.

Wang, G, Liang, Q, Shi, F, Zheng, J (2021) Analytical and numerical investigation of trapped ocean waves along a submerged ridge, Journal of Fluid Mechanics, 915, A54, ISSN: 0022-1120. DOI: 10.1017/jfm.2020.1039.

Jiang, J, Liang, Q, Xia, X, Hou, J (Accepted for publication) A coupled hydrodynamic and particle-tracking model for full-process simulation of nonpoint source pollutants, Environmental Modelling & Software, 136, pp.104951-104951, ISSN: 1364-8152. DOI: 10.1016/j.envsoft.2020.104951.

Özgen-Xian, I, Xia, X, Liang, Q, Hinkelmann, R, Liang, D, Hou, J (2021) Innovations towards the next generation of shallow flow models, Advances in Water Resources, 149, 103867, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2021.103867.

Pramanik, M, Chowdhury, K, Rana, MJ, Bisht, P, Pal, R, Szabo, S, Pal, I, Behera, B, Liang, Q, Padmadas, SS, Udmale, P (2020) Climatic influence on the magnitude of COVID-19 outbreak: a stochastic model-based global analysis, International Journal of Environmental Health Research, ISSN: 0960-3123. DOI: 10.1080/09603123.2020.1831446.

Kabir, S, Patidar, S, Xia, X, Liang, Q, Neal, J, Pender, G (2020) A deep convolutional neural network model for rapid prediction of fluvial flood inundation, Journal of Hydrology, 590, 125481, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2020.125481.

Chen, H, Liang, Q, Liang, Z, Liu, Y, Ren, T (2020) Extraction of connected river networks from multi-temporal remote sensing imagery using a path tracking technique, Remote Sensing of Environment, 246, pp.111868-111868, ISSN: 0034-4257. DOI: 10.1016/j.rse.2020.111868.

Zounemat-Kermani, M, Matta, E, Cominola, A, Xia, X, Zhang, Q, Liang, Q, Hinkelmann, R (2020) Neurocomputing in surface water hydrology and hydraulics: A review of two decades retrospective, current status and future prospects, Journal of Hydrology, 588, pp.125085-125085, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2020.125085.

Ming, X, Liang, Q, Xia, X, Li, D, Fowler, HJ (2020) Real‐time flood forecasting based on a high‐performance 2D hydrodynamic model and numerical weather predictions, Water Resources Research, 56(7), e2019WR025583, ISSN: 0043-1397. DOI: 10.1029/2019wr025583.

Wang, F, Wang, Z, Yang, H, Di, D, Zhao, Y, Liang, Q (2020) A new copula-based standardized precipitation evapotranspiration streamflow index for drought monitoring, Journal of Hydrology, 585, pp.124793-124793, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2020.124793.

Wang, F, Wang, Z, Yang, H, Di, D, Zhao, Y, Liang, Q (2020) Utilizing GRACE-based groundwater drought index for drought characterization and teleconnection factors analysis in the North China Plain, Journal of Hydrology, 585, pp.124849-124849, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2020.124849.

Jiang, L, Hu, Y, Xia, X, Liang, Q, Soltoggio, A, Kabir, S (2020) A multi-scale mapping approach based on a deep learning CNN model for reconstructing high-resolution urban DEMs, Water, 12(5), 1369, DOI: 10.3390/w12051369.

Wang, F, Wang, Z, Yang, H, Di, D, Zhao, Y, Liang, Q, Hussain, Z (2020) Comprehensive evaluation of hydrological drought and its relationships with meteorological drought in the Yellow River basin, China, Journal of Hydrology, 584, pp.124751-124751, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2020.124751.

Hou, J, Li, B, Tong, Y, Ma, L, Ball, J, Luo, H, Liang, Q, Xia, J (2020) Cause analysis for a new type of devastating flash flood, Hydrology Research, 51(1), pp.1-16, ISSN: 1998-9563. DOI: 10.2166/nh.2019.091.

Li, Q, Liang, Q, Xia, X (2020) A novel 1D-2D coupled model for hydrodynamic simulation of flows in drainage networks, Advances in Water Resources, 137, pp.103519-103519, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2020.103519.

Xiong, Y, Mahaffey, S, Liang, Q, Rouainia, M, Wang, G (2019) A new 1D coupled hydrodynamic discrete element model for floating debris in violent shallow flows, Journal of Hydraulic Research, ISSN: 0022-1686. DOI: 10.1080/00221686.2019.1671513.

Cui, Y, Liang, Q, Wang, G, Zhao, J, Hu, J, Wang, Y, Xia, X (2019) Simulation of Hydraulic Structures in 2D High-Resolution Urban Flood Modeling, Water, 11(10), pp.2139-2139, DOI: 10.3390/w11102139.

Dang, C-H, Wang, J, Liang, Q (2019) Inflows/outflows driven particle dynamics in an idealised lake, Journal of Hydrodynamics, 31(5), pp.873-886, ISSN: 1001-6058. DOI: 10.1007/s42241-019-0070-9.

Xia, X, Liang, Q, Ming, X (2019) A full-scale fluvial flood modelling framework based on a high-performance integrated hydrodynamic modelling system (HiPIMS), Advances in Water Resources, 132, 103392, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2019.103392.

Lin, L, Wu, Z, Liang, Q (2019) Urban flood susceptibility analysis using a GIS-based multi-criteria analysis framework, Natural Hazards, 97(2), pp.455-475, ISSN: 0921-030X. DOI: 10.1007/s11069-019-03615-2.

Chen, H, Liang, Q, Liang, Z, Liu, Y, Xie, S (2019) Remote-sensing disturbance detection index to identify spatio-temporal varying flood impact on crop production, Agricultural and Forest Meteorology, 269-270, pp.180-191, ISSN: 0168-1923. DOI: 10.1016/j.agrformet.2019.02.002.

Wang, G, Liang, Q, Zheng, J, Wan, P (2019) A new multilayer nonhydrostatic formulation for surface water waves, Journal of Coastal Research, 35(3), pp.693-710, ISSN: 0749-0208. DOI: 10.2112/JCOASTRES-D-18-00022.1.

Xiong, Y, Liang, Q, Park, H, Cox, D, Wang, G (2019) A deterministic approach for assessing tsunami-induced building damage through quantification of hydrodynamic forces, Coastal Engineering, 144, pp.1-14, ISSN: 0378-3839. DOI: 10.1016/j.coastaleng.2018.11.002.

Liu, Z, Zhang, H, Liang, Q (2018) A coupled hydrological and hydrodynamic model for flood simulation, Hydrology Research, ISSN: 0029-1277. DOI: 10.2166/nh.2018.090.

Jiang, L, Ling, D, Zhao, M, Wang, C, Liang, Q, Liu, K (2018) Effective identification of terrain positions from gridded DEM data using multimodal classification integration, ISPRS International Journal of Geo-Information, 7(11), DOI: 10.3390/ijgi7110443.

Hou, J, Wang, R, Liang, Q, Li, Z, Huang, MS, Hinkelmann, R (2018) Efficient surface water flow simulation on static Cartesian grid with local refinement according to key topographic features, Computers & Fluids, 176, pp.117-134, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2018.03.024.

Hou, J, Guo, K, Liu, F, Han, H, Liang, Q, Tong, Y, Li, P (2018) Assessing Slope Forest Effect on Flood Process Caused by a Short-Duration Storm in a Small Catchment, Water, 10(9), pp.1256-1256, DOI: 10.3390/w10091256.

Xia, X and Liang, Q (2018) A new efficient implicit scheme for discretising the stiff friction terms in the shallow water equations, Advances in Water Resources, 117, pp.87-97, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2018.05.004.

Wang, G, Fu, D, Zheng, J, Liang, Q, Zhang, Y (2018) Analytic study on long wave transformation over a seamount with a pit, Ocean Engineering, 154, pp.167-176, ISSN: 0029-8018. DOI: 10.1016/j.oceaneng.2018.02.012.

Chen, H, Liang, Q, Liu, Y, Xie, S (2018) Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling, Journal of Hydrology, 559, pp.56-70, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2018.01.056.

Hou, J, Li, G, Li, G, Liang, Q, Zhi, Z (2018) Application of efficient high-resolution hydrodynamic model to simulations of flood propagation, Shuili Fadian Xuebao/Journal of Hydroelectric Engineering, 37(2), pp.96-107, ISSN: 1003-1243. DOI: 10.11660/slfdxb.20180210.

Wang, G, Zheng, J, Liang, Q (2018) Accuracy of depth-integrated nonhydrostatic wave models, Ocean Engineering, 149, pp.217-225, ISSN: 0029-8018. DOI: 10.1016/j.oceaneng.2017.12.015.

Xia, X and Liang, Q (2018) A new depth-averaged model for flow-like landslides over complex terrains with curvatures and steep slopes, Engineering Geology, 234, pp.174-191, ISSN: 0013-7952. DOI: 10.1016/j.enggeo.2018.01.011.

Xia, X, Liang, Q, Ming, X, Hou, J (2018) Reply to comment by Lu et al. on “An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations”, Water Resources Research, 54(1), pp.628-630, ISSN: 0043-1397. DOI: 10.1002/2017WR021696.

Xiong, Y, Liang, Q, Mahaffey, S, Rouainia, M, Wang, G (2018) A novel two-way method for dynamically coupling a hydrodynamic model with a discrete element model (DEM), Journal of Hydrodynamics, 30(5), pp.966-969, ISSN: 1001-6058. DOI: 10.1007/s42241-018-0081-y.

Xing, Y, Liang, Q, Wang, G, Ming, X, Xia, X (2018) City-scale hydrodynamic modelling of urban flash floods: the issues of scale and resolution, Natural Hazards, ISSN: 0921-030X. DOI: 10.1007/s11069-018-3553-z.

Hou, J-M, Liang, Q-H, Wang, G, Hinkelmann, R (2017) Preface for special section on flood modeling and resilience, Water Science and Engineering, 10(4), pp.265-266, ISSN: 1674-2370. DOI: 10.1016/j.wse.2017.12.008.

Yang, H-B, Li, E-C, Zhao, Y, Liang, Q-H (2017) Effect of water-sediment regulation and its impact on coastline and suspended sediment concentration in Yellow River Estuary, Water Science and Engineering, 10(4), pp.311-319, ISSN: 1674-2370. DOI: 10.1016/j.wse.2017.12.009.

Hou, J-M, Wang, R, Jing, H-X, Zhang, X, Liang, Q-H, Di, Y-Y (2017) An efficient dynamic uniform Cartesian grid system for inundation modeling, Water Science and Engineering, 10(4), pp.267-274, ISSN: 1674-2370. DOI: 10.1016/j.wse.2017.12.004.

Chen, H, Liang, Z, Liu, Y, Liang, Q, Xie, S (2017) Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields, Journal of Hydrology, 553, pp.262-275, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2017.08.001.

Xia, X, Liang, Q, Ming, X, Hou, J (2017) An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations, Water Resources Research, 53(5), pp.3730-3759, ISSN: 0043-1397. DOI: 10.1002/2016WR020055.

Birkinshaw, SJ, Guerreiro, SB, Nicholson, A, Liang, Q, Quinn, P, Zhang, L, He, B, Yin, J, Fowler, HJ (2017) Climate change impacts on Yangtze River discharge at the Three Gorges Dam, Hydrology and Earth System Sciences, 21(4), pp.1911-1927, DOI: 10.5194/hess-21-1911-2017.

LIANG, Q, SMITH, L, XIA, X (2016) New prospects for computational hydraulics by leveraging high-performance heterogeneous computing techniques, Journal of Hydrodynamics, Ser. B, 28(6), pp.977-985, ISSN: 1001-6058. DOI: 10.1016/S1001-6058(16)60699-6.

Lai, X, Liang, Q, Huang, Q, Jiang, J, Lu, XX (2016) Numerical evaluation of flow regime changes induced by the Three Gorges Dam in the Middle Yangtze, Hydrology Research, 47(S1), pp.149-160, ISSN: 0029-1277. DOI: 10.2166/nh.2016.158.

Guan, M and Liang, Q (2016) A two-dimensional hydro-morphological model for river hydraulics and morphology with vegetation, Environmental Modelling and Software, 88, pp.10-21, ISSN: 1364-8152. DOI: 10.1016/j.envsoft.2016.11.008.

Amouzgar, R, Liang, Q, Clarke, P, Yasuda, T, Mase, H (2016) Computationally Efficient Tsunami Modeling on Graphics Processing Units (GPUs), International Journal of Offshore and Polar Engineering, 26(2), pp.154-160, ISSN: 1053-5381. DOI: 10.17736/ijope.2016.ak10.

Ferrer-Boix, C and Liang, Q (2016) A numerical approach for analysing the performance of a sewage screening chamber, Urban Water Journal, 13(4), pp.360-371, ISSN: 1573-062X. DOI: 10.1080/1573062x.2014.993991.

LIANG, Q, CHEN, K-C, HOU, J, XIONG, Y, WANG, G, QIANG, J (2016) Hydrodynamic modelling of flow impact on structures under extreme flow conditions, Journal of Hydrodynamics, Ser. B, 28(2), pp.267-274, ISSN: 1001-6058. DOI: 10.1016/S1001-6058(16)60628-5.

Hou, J, Liang, Q, Xia, X (2015) Robust absorbing boundary conditions for shallow water flow models, Environmental Earth Sciences, 74(11), pp.7407-7422, ISSN: 1866-6280. DOI: 10.1007/s12665-015-4743-6.

Liang, Q, Xia, X, Hou, J (2015) Efficient urban flood simulation using a GPU-accelerated SPH model, Environmental Earth Sciences, 74(11), pp.7285-7294, ISSN: 1866-6280. DOI: 10.1007/s12665-015-4753-4.

Liang, Q, Hou, J, Amouzgar, R (2015) Simulation of Tsunami Propagation Using Adaptive Cartesian Grids, Coastal Engineering Journal, 57(4), ISSN: 2166-4250. DOI: 10.1142/s0578563415500163.

Wang, G, Zheng, J-H, Liang, Q-H, Zhang, W, Huang, C (2015) Theoretical analysis of harbor resonance in harbor with an exponential bottom profile, China Ocean Engineering, 29(6), pp.821-834, ISSN: 0890-5487. DOI: 10.1007/s13344-015-0058-3.

Hinkelmann, R, Liang, Q, Aizinger, V, Dawson, C (2015) Robust shallow water models, Environmental Earth Sciences, 74(11), pp.7273-7274, ISSN: 1866-6280. DOI: 10.1007/s12665-015-4764-1.

Xia, X and Liang, Q (2015) A GPU-accelerated smoothed particle hydrodynamics (SPH) model for the shallow water equations, Environmental Modelling & Software, 75, pp.28-43, ISSN: 1364-8152. DOI: 10.1016/j.envsoft.2015.10.002.

Hou, J, Liang, Q, Li, Z, Wang, S, Hinkelmann, R (2015) Numerical error control for second-order explicit TVD scheme with limiters in advection simulation, Computers & Mathematics with Applications, 70(9), pp.2197-2209, ISSN: 0898-1221. DOI: 10.1016/j.camwa.2015.08.022.

Liang, Q and Smith, LS (2015) A high-performance integrated hydrodynamic modelling system for urban flood simulations, Journal of Hydroinformatics, 17(4), pp.518-533, ISSN: 1464-7141. DOI: 10.2166/hydro.2015.029.

Liang, Q, Hou, J, Xia, X (2015) Contradiction between the C‐property and mass conservation in adaptive grid based shallow flow models: cause and solution, International Journal for Numerical Methods in Fluids, 78(1), pp.17-36, ISSN: 0271-2091. DOI: 10.1002/fld.4005.

Smith, L, Liang, Q, James, P, Lin, W (2015) Assessing the utility of social media as a data source for flood risk management using a real-time modelling framework, Journal of Flood Risk Management, 10(3), pp.370-380, ISSN: 1753-318X. DOI: 10.1111/jfr3.12154.

Zhang, L, Liang, Q, Wang, Y, Yin, J (2015) A robust coupled model for solute transport driven by severe flow conditions, Journal of Hydro-environment Research, 9(1), pp.49-60, ISSN: 1570-6443. DOI: 10.1016/j.jher.2014.04.005.

Kesserwani, G and Liang, Q (2015) RKDG2 shallow-water solver on non-uniform grids with local time steps: Application to 1D and 2D hydrodynamics, Applied Mathematical Modelling, 39(3-4), pp.1317-1340, ISSN: 0307-904X. DOI: 10.1016/j.apm.2014.08.009.

Hou, J, Liang, Q, Zhang, H, Hinkelmann, R (2015) An efficient unstructured MUSCL scheme for solving the 2D shallow water equations, Environmental Modelling & Software, 66, pp.131-152, ISSN: 1364-8152. DOI: 10.1016/j.envsoft.2014.12.007.

Smith, LS, Liang, Q, Quinn, PF (2015) Towards a hydrodynamic modelling framework appropriate for applications in urban flood assessment and mitigation using heterogeneous computing, Urban Water Journal, 12(1), pp.67-78, ISSN: 1573-062X. DOI: 10.1080/1573062x.2014.938763.

Lu, D, Wang, B, Wang, Y, Zhou, H, Liang, Q, Peng, Y, Roskilly, T (2015) Optimal operation of cascade hydropower stations using hydrogen as storage medium, Applied Energy, 137, pp.56-63, ISSN: 0306-2619. DOI: 10.1016/j.apenergy.2014.09.092.

Hou, J, Liang, Q, Zhang, H, Hinkelmann, R (2014) Multislope MUSCL method applied to solve shallow water equations, Computers & Mathematics with Applications, 68(12), pp.2012-2027, ISSN: 0898-1221. DOI: 10.1016/j.camwa.2014.09.018.

Lai, X, Liang, Q, Yesou, H, Daillet, S (2014) Variational assimilation of remotely sensed flood extents using a 2-D flood model, Hydrology and Earth System Sciences, 18(11), pp.4325-4339, DOI: 10.5194/hess-18-4325-2014.

Lai, X, Liang, Q, Jiang, J, Huang, Q (2014) Impoundment Effects of the Three-Gorges-Dam on Flow Regimes in Two China’s Largest Freshwater Lakes, Water Resources Management, 28(14), pp.5111-5124, ISSN: 0920-4741. DOI: 10.1007/s11269-014-0797-6.

Zhang, H, Wang, Y, Liang, Q, Smith, LS, Kilsby, CG (2014) Non-negative depth reconstruction for a two-dimensional partial inertial inundation model, Journal of Hydroinformatics, 16(5), pp.1158-1177, ISSN: 1464-7141. DOI: 10.2166/hydro.2014.131.

Wang, G, Zheng, J, Liang, Q, Zheng, Y (2014) Analytical solutions for oscillations in a harbor with a hyperbolic-cosine squared bottom, Ocean Engineering, 83, pp.16-23, ISSN: 0029-8018. DOI: 10.1016/j.oceaneng.2014.03.027.

Hou, J, Simons, F, Liang, Q, Hinkelmann, R (2014) An improved hydrostatic reconstruction method for shallow water model, Journal of Hydraulic Research, 52(3), pp.432-439, ISSN: 0022-1686. DOI: 10.1080/00221686.2013.858648.

Smith, LS and Liang, Q (2013) Towards a generalised GPU/CPU shallow-flow modelling tool, Computers & Fluids, 88, pp.334-343, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2013.09.018.

Xia, X, Liang, Q, Pastor, M, Zou, W, Zhuang, Y-F (2013) Balancing the source terms in a SPH model for solving the shallow water equations, Advances in Water Resources, 59, pp.25-38, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2013.05.004.

Hou, J, Liang, Q, Simons, F, Hinkelmann, R (2013) A stable 2D unstructured shallow flow model for simulations of wetting and drying over rough terrains, Computers & Fluids, 82, pp.132-147, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2013.04.015.

Lai, X, Jiang, J, Liang, Q, Huang, Q (2013) Large-scale hydrodynamic modeling of the middle Yangtze River Basin with complex river–lake interactions, Journal of Hydrology, 492, pp.228-243, ISSN: 0022-1694. DOI: 10.1016/j.jhydrol.2013.03.049.

Li, G, Gao, J, Liang, Q (2013) A well‐balanced weighted essentially non‐oscillatory scheme for pollutant transport in shallow water, International Journal for Numerical Methods in Fluids, 71(12), pp.1566-1587, ISSN: 0271-2091. DOI: 10.1002/fld.3726.

Duran, A, Liang, Q, Marche, F (2013) On the well-balanced numerical discretization of shallow water equations on unstructured meshes, Journal of Computational Physics, 235, pp.565-586, ISSN: 0021-9991. DOI: 10.1016/j.jcp.2012.10.033.

Hou, J, Liang, Q, Simons, F, Hinkelmann, R (2013) A 2D well-balanced shallow flow model for unstructured grids with novel slope source term treatment, Advances in Water Resources, 52, pp.107-131, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2012.08.003.

Zhang, C, Liang, Q, Yin, J (2013) A first-order adaptive solution to rapidly spreading flood waves, Progress in Computational Fluid Dynamics, An International Journal, 13(1), pp.1-1, ISSN: 1468-4349. DOI: 10.1504/pcfd.2013.050645.

Liang, Q (2012) A simplified adaptive Cartesian grid system for solving the 2D shallow water equations, International Journal for Numerical Methods in Fluids, 69(2), pp.442-458, ISSN: 0271-2091. DOI: 10.1002/fld.2568.

Kesserwani, G and Liang, Q (2012) Dynamically adaptive grid based discontinuous Galerkin shallow water model, Advances in Water Resources, 37, pp.23-39, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2011.11.006.

Kesserwani, G and Liang, Q (2012) Influence of Total-Variation-Diminishing Slope Limiting on Local Discontinuous Galerkin Solutions of the Shallow Water Equations, Journal of Hydraulic Engineering, 138(2), pp.216-222, ISSN: 0733-9429. DOI: 10.1061/(asce)hy.1943-7900.0000494.

Kesserwani, G and Liang, Q (2012) Locally Limited and Fully Conserved RKDG2 Shallow Water Solutions with Wetting and Drying, Journal of Scientific Computing, 50(1), pp.120-144, ISSN: 0885-7474. DOI: 10.1007/s10915-011-9476-4.

Wang, Y, Liang, Q, Kesserwani, G, Hall, JW (2011) A positivity-preserving zero-inertia model for flood simulation, Computers & Fluids, 46(1), pp.505-511, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2011.01.026.

Alias, NA, Liang, Q, Kesserwani, G (2011) A Godunov-type scheme for modelling 1D channel flow with varying width and topography, Computers & Fluids, 46(1), pp.88-93, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2010.12.009.

Liang, Q (2011) A structured but non‐uniform Cartesian grid‐based model for the shallow water equations, International Journal for Numerical Methods in Fluids, 66(5), pp.537-554, ISSN: 0271-2091. DOI: 10.1002/fld.2266.

Wang, J and Liang, Q (2011) Testing a new adaptive grid‐based shallow flow model for different types of flood simulations, Journal of Flood Risk Management, 4(2), pp.96-103, ISSN: 1753-318X. DOI: 10.1111/j.1753-318x.2011.01094.x.

Liang, Q (2011) A Coupled Morphodynamic Model for Applications Involving Wetting and Drying, Journal of Hydrodynamics, 23(3), pp.273-281, ISSN: 1001-6058. DOI: 10.1016/s1001-6058(10)60113-8.

Wang, Y, Liang, Q, Kesserwani, G, Hall, JW (2011) A 2D shallow flow model for practical dam-break simulations, Journal of Hydraulic Research, 49(3), pp.307-316, ISSN: 0022-1686. DOI: 10.1080/00221686.2011.566248.

Kesserwani, G and Liang, Q (2011) A conservative high‐order discontinuous Galerkin method for the shallow water equations with arbitrary topography, International Journal for Numerical Methods in Engineering, 86(1), pp.47-69, ISSN: 0029-5981. DOI: 10.1002/nme.3044.

Liang, Q (2011) Dynamically adaptive simulation of coastal hydrodynamics, International Journal of Offshore and Polar Engineering, 21(1), pp.50-55, ISSN: 1053-5381.

Kesserwani, G and Liang, Q (2010) Well-balanced RKDG2 solutions to the shallow water equations over irregular domains with wetting and drying, Computers & Fluids, 39(10), pp.2040-2050, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2010.07.008.

Kesserwani, G and Liang, Q (2010) A discontinuous Galerkin algorithm for the two-dimensional shallow water equations, Computer Methods in Applied Mechanics and Engineering, 199(49-52), pp.3356-3368, ISSN: 0045-7825. DOI: 10.1016/j.cma.2010.07.007.

Kesserwani, G, Vazquez, J, Rivière, N, Liang, Q, Travin, G, Mosé, R (2010) New Approach for Predicting Flow Bifurcation at Right-Angled Open-Channel Junction, Journal of Hydraulic Engineering, 136(9), pp.662-668, ISSN: 0733-9429. DOI: 10.1061/(asce)hy.1943-7900.0000222.

Liang, Q (2010) Flood Simulation Using a Well-Balanced Shallow Flow Model, Journal of Hydraulic Engineering, 136(9), pp.669-675, ISSN: 0733-9429. DOI: 10.1061/(asce)hy.1943-7900.0000219.

Liang, Q (2010) A Well-balanced and Non-negative Numerical Scheme for Solving the Integrated Shallow Water and Solute Transport Equations, Communications in Computational Physics, 7(5), pp.1049-1075, ISSN: 1815-2406. DOI: 10.4208/cicp.2009.09.156.

REN, M, WANG, B, LIANG, Q, FU, G (2010) Classified real-time flood forecasting by coupling fuzzy clustering and neural network, International Journal of Sediment Research, 25(2), pp.134-148, ISSN: 1001-6279. DOI: 10.1016/s1001-6279(10)60033-9.

Liang, Q, Wang, Y, Archetti, R (2010) A well-balanced shallow flow solver for coastal simulations, International Journal of Offshore and Polar Engineering, 20(1), pp.41-47, ISSN: 1053-5381.

Kesserwani, G, Liang, Q, Vazquez, J, Mosé, R (2010) Well‐balancing issues related to the RKDG2 scheme for the shallow water equations, International Journal for Numerical Methods in Fluids, 62(4), pp.428-448, ISSN: 0271-2091. DOI: 10.1002/fld.2027.

Liang, Q and Marche, F (2009) Numerical resolution of well-balanced shallow water equations with complex source terms, Advances in Water Resources, 32(6), pp.873-884, ISSN: 0309-1708. DOI: 10.1016/j.advwatres.2009.02.010.

Liang, Q and Borthwick, AGL (2009) Adaptive quadtree simulation of shallow flows with wet–dry fronts over complex topography, Computers & Fluids, 38(2), pp.221-234, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2008.02.008.

Liang, Q, Taylor, PH, Borthwick, AGL (2009) Particle mixing and reactive front motions in chaotic but closed shallow flows, Computers & Fluids, 38(2), pp.382-392, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2008.04.011.

Liang, Q, Du, G, Hall, JW, Borthwick, AG (2008) Flood Inundation Modeling with an Adaptive Quadtree Grid Shallow Water Equation Solver, Journal of Hydraulic Engineering, 134(11), pp.1603-1610, ISSN: 0733-9429. DOI: 10.1061/(asce)0733-9429(2008)134:11(1603).

Ning, DZ, Zang, J, Liang, Q, Taylor, PH, Borthwick, AGL (2008) Boussinesq cut‐cell model for non‐linear wave interaction with coastal structures, International Journal for Numerical Methods in Fluids, 57(10), pp.1459-1483, ISSN: 0271-2091. DOI: 10.1002/fld.1656.

Liang, Q and Borthwick, AGL (2008) Simple treatment of non‐aligned boundaries in a Cartesian grid shallow flow model, International Journal for Numerical Methods in Fluids, 56(11), pp.2091-2110, ISSN: 0271-2091. DOI: 10.1002/fld.1615.

Liang, Q (2008) Simulation of Shallow Flows in Nonuniform Open Channels, Journal of Fluids Engineering, 130(1), ISSN: 0098-2202. DOI: 10.1115/1.2829593.

Zang, J, Ning, D, Liu, S, Liang, Q, Taylor, PH, Taylor, RE, Borthwick, AGL (2007) Boussinesq cut-cell model for wave scattering from cylinder in shallow water, International Journal of Offshore and Polar Engineering, 17(4), pp.266-269, ISSN: 1053-5381.

Liang, Q, Zang, J, Borthwick, AGL, Taylor, PH (2007) Shallow flow simulation on dynamically adaptive cut cell quadtree grids, International Journal for Numerical Methods in Fluids, 53(12), pp.1777-1799, ISSN: 0271-2091. DOI: 10.1002/fld.1363.

Liang, Q, Taylor, PH, Borthwick, AGL (2007) Particle mixing and reactive front motion in unsteady open shallow flow – Modelled using singular value decomposition, Computers & Fluids, 36(2), pp.248-258, ISSN: 0045-7930. DOI: 10.1016/j.compfluid.2006.01.018.

Liang, Q, Borthwick, AGL, Taylor, PH (2006) Wind-induced chaotic advection in shallow flow geometries. Part II: Non-circular basins, Journal of Hydraulic Research, 44(2), pp.180-188, ISSN: 0022-1686. DOI: 10.1080/00221686.2006.9521674.

Liang, Q, Borthwick, AGL, Taylor, PH (2006) Wind-induced chaotic advection in shallow flow geometries. Part I: Circular basins, Journal of Hydraulic Research, 44(2), pp.170-179, ISSN: 0022-1686. DOI: 10.1080/00221686.2006.9521673.

Liang, Q, Borthwick, AGL, Taylor, PH (2005) Chaotic mixing in a basin due to a sinusoidal wind field, International Journal for Numerical Methods in Fluids, 47(8-9), pp.871-877, ISSN: 0271-2091. DOI: 10.1002/fld.880.

Liang, Q, Borthwick, AGL, Stelling, G (2004) Simulation of dam‐ and dyke‐break hydrodynamics on dynamically adaptive quadtree grids, International Journal for Numerical Methods in Fluids, 46(2), pp.127-162, ISSN: 0271-2091. DOI: 10.1002/fld.748.

Conferences

Xiong, Y, Liang, Q, Tong, X, Zheng, J, Wang, G (2022) Modelling Floating Debris Transport in a Flash Flood Event. In , Proceedings of the IAHR World Congress, pp.327-334, DOI: 10.3850/IAHR-39WC2521716X2022121.

Wang, G, Yu, H, Zheng, J, Liang, Q (2020) The ray paths of trapped waves over the submerged ridge. In , APAC 2019 - Proceedings of the 10th International Conference on Asian and Pacific Coasts, pp.169-173, ISBN: 9789811502903. DOI: 10.1007/978-981-15-0291-0_24.

Cui, Y, Liang, Q, Wang, G, Hu, J, Wang, Y (2019) SIMULATION OF HYDRAULIC STRUCTURES IN 2D HIGH-RESOLUTION URBAN FLOOD MODELING. In , Proceedings of the IAHR World Congress, pp.895-903, DOI: 10.3850/38WC092019-055.

Liang, Q, Ming, X, Xia, X (2019) A HIGH-PERFORMANCE INTEGRATED HYDRODYNAMIC MODELLING SYSTEM FOR REAL-TIME FLOOD FORECASTING. In , Proceedings of the IAHR World Congress, pp.5246-5255, DOI: 10.3850/38WC092019-0969.

Wang, G, Hu, J, Zheng, JH, Liang, QH (2018) Trapped waves over the hyperbolic-cosine ocean ridge. In The 9th International Conference on APAC, Proceedings of the 9th International Conference on APAC 2017, Pasay City, Philippines, pp.44-54, ISBN: 9789813233805.

Liang, Q, Xia, X, Hou, J (2016) Catchment-scale High-resolution Flash Flood Simulation Using the GPU-based Technology. In , Procedia Engineering, pp.975-981, DOI: 10.1016/j.proeng.2016.07.585.

Rashid, AA, Liang, Q, Dawson, RJ, Smith, LS (2016) Calibrating a High-Performance Hydrodynamic Model for Broad-Scale Flood Simulation: Application to Thames Estuary, London, UK. In , Procedia Engineering, pp.967-974, DOI: 10.1016/j.proeng.2016.07.584.

Hou, J, Li, Z, Liang, Q, Li, G, Cheng, W, Wang, W, Wang, R (2016) Effects of Morphological Change on Fluvial Flood Patterns Evaluated by a Hydro-geomorphological Model. In , Procedia Engineering, pp.441-449, DOI: 10.1016/j.proeng.2016.07.536.

Xing, Y, Yang, S, Zhou, H, Liang, Q (2016) Effect of Floodplain Roughness on Velocity Distribution in Mountain Rivers. In , Procedia Engineering, pp.467-475, DOI: 10.1016/j.proeng.2016.07.539.

Liang, Q and Amouzgar, R (2016) Performance of different hardware devices for tsunami simulations. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.709-715, ISBN: 9781880653883.

Xiong, Y, Liang, Q, Amouzgar, R, Cox, DT, Mori, N, Wang, G, Zheng, J (2016) High-performance simulation of tsunami inundation and impact on building structures. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.732-738, ISBN: 9781880653883.

Chen, K, Liang, Q, Xiong, Y, Qiang, J, Wang, G, Zheng, J (2016) Laboratory and numerical investigation of extreme flow impact on simplified sea-crossing bridge structures. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.400-407, ISBN: 9781880653883.

Qiang, J, Liang, Q, Wang, G, Zheng, J (2016) Testing a shock-capturing hydrodynamic model for storm surge simulation. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.747-753, ISBN: 9781880653883.

Amouzgar, R and Liang, Q (2014) Application of a GPU based hydrodynamic model in tsunami simulations. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.10-16, ISBN: 9781880653913.

Al-Bourae, Y, Downie, M, Liang, Q (2013) 3D numerical reconstruction of the hydrodynamics around an artificial reef in Loch Linnhe, Scotland. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.522-528, ISBN: 9781880653999.

Liang, Q, Yamada, F, Tsujimoto, G, Zheng, J (2013) Combined physical and numerical modeling study of surge impact on structures. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.648-653, ISBN: 9781880653999.

Al-Bourae, Y, Liang, Q, Downie, M (2012) Tidal simulation in loch linnhe using a finite volume shallow flow model. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.801-807, ISBN: 9781880653944.

Liang, QH (2011) A new coupled model for simulating shallow flow driven morphological change. In , AIP Conference Proceedings, pp.319-322, ISBN: 9780735409361. DOI: 10.1063/1.3651908.

Liang, Q (2010) A new adaptive grid based shallow water equation solver for coastal hydrodynamic modeling. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.768-774, ISBN: 9781880653777.

Wu, X, Hall, J, Liang, Q (2010) Coastal flood inundation modelling with a 2-D shallow water equation solver. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.871-875, ISBN: 9781880653777.

Liang, Q, Wang, Y, Archetti, R (2009) Modeling coastal run-up using a well-balanced shallow flow solver. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.771-778, ISBN: 9781880653531.

Zang, J, Ning, D, Liu, S, Liang, Q, Taylor, PH, Eatock Taylor, R, Borthwick, AGL (2007) A new Boussinesq model for wave run-up on curved structures using Cartesian cut-cell grids. In , Proceedings of the International Offshore and Polar Engineering Conference, pp.2084-2091, ISBN: 9781880653685.

Liang, Q, Zang, J, Borthwick, AGL, Taylor, PH, Shuxue, L, Smith, C (2006) Numerical simulation of non-linear wave interaction with an offshore wind turbine foundation. In , Proceedings of the Seventh 2006 ISOPE Pacific/Asia Offshore Mechanics Symposium, ISOPE PACOMS 2006, pp.231-236, ISBN: 9781880653678.

Hill, B, Liang, Q, Chen, H, Boscher, L (Accepted for publication) Natural flood management site-scale data: remote challenges with remote controlled solutions. In .

Chapters

Wu, XZ, Hall, JW, Liang, Q, Dawson, RJ (2015) Broadscale coastal inundation modelling. In Broad Scale Coastal Simulation: New Techniques to Understand and Manage Shorelines in the Third Millennium, pp.213-232, ISBN: 9789400752573. DOI: 10.1007/978-94-007-5258-0_8.

Datasets

Chen, H, Liang, Q, Liang, Z, Liu, Y, Ren, T (2021) Supplementary information files for Extraction of connected river networks from multi-temporal remote sensing imagery using a path tracking technique, DOI: 10.17028/rd.lboro.12656828.

Other

Wei, ZL, Shang, YQ, Liang, QH, Xia, XL (2023) Supplementary material to "A coupled hydrological and hydrodynamic modelling approach for estimating rainfall thresholds of debris-flow occurrence". DOI: 10.5194/nhess-2023-180-supplement.

Su, X, Liang, Q, Jiang, J (2023) Calibrating a 2D high-performance hydrodynamic model for fluvial process modelling along the Mekong River, The Vietnamese Mekong Delta (VMD), representing a highly complex hydrodynamic system, plays a major role in food security and socio-economic development in Vietnam. With ongoing climate change and rapid urbanization, the VMD is increasingly vulnerable to flood risk from multiple sources, e.g. driven simultaneously by fluvial, pluvial and coastal processes. It is essential to develop reliable modelling tools to simulate such compound flooding processes to support hazard risk assessment and management to inform the development of policies and effective strategies to sustain the delta development.To support reliable compound flood modelling and risk assessment in VMD, it is important to accurately predict the fluvial processes along the Mekong River. For large river and river network modelling, one-dimensional (1D) and quasi two-dimensional (2D) hydrodynamic models are commonly used. However, modelling overbank flow and flooding process over floodplains is out of the capability of these 1D or even quasi 2D models. These 1D or quasi 2D models are then integrated with a 2D inundation model through one-way coupling to predict the flooding processes in floodplains. The resulting one-way coupled models neglect the dynamic interactions between the flows in the river and floodplain as well as upstream and downstream domains, inevitable introducing model uncertainties that are difficult to quantified and controlled. Ideally, we can use a full 2D hydrodynamic model to simulate the entirely fluvial flooding process spreading from the river channels over to the floodplains. However, this approach has not been widely reported for large-scale application due to the prohibited computational cost of a 2D hydrodynamic model.In this work, we explore the possibility of calibrating a fully 2D hydrodynamic model, the High-Performance Integrated hydrodynamic Modelling System (HiPIMS), to reproduce high, medium and low flood conditions along the middle and lower reaches of Mekong River of 55 km, starting from the Kratie gauge in Cambodia to avoid tidal influence. The model is driven by inflow at Kratie and calibrated using the measurements of both water level and discharge available at 4 gauge stations (Can Tho, My Thuan, Chau Doc, Tan Chau). The Nash-Sutcliffe efficiency (NSE) is used to quantify prediction errors to support the model calibration process.. DOI: 10.5194/egusphere-egu23-16380.

Xia, X, Jarsve, K, Dijkstra, T, Liang, Q, Meng, X (2023) An integrated hydrodynamic model for flash flood and debris flow simulations, Climate change is forecasted to result in more frequent and intense storms, which in turn are likely to cause more flash floods and other hazardous processes in steep hilly and mountainous catchments. These flash floods are driven by complex and rapid overland flow responses to intense rainfall across these catchments. Where loose slope or valley-based deposits are available, flood water may mobilise these materials and transform into dynamic high-velocity, high-density debris flows that can pose significant threats to people, property, and infrastructure considerable distances away from the areas where these deposits are mobilised, exacerbating the already devastating situation caused by flooding. Hydro-dynamic models solving the full shallow water equations (SWEs) have shown great potential to reliably simulate the dynamics of overland flows and flash floods at catchment scales. However, simulating the transition from flash flood into debris flow is still technically challenging because of the difficulty of simulating erosion and deposition processes robustly. A reason is that the commonly used method for calculating erosion and deposition rate may suffer from singularity in the presence of vanishing velocity, which poses a major challenge for practical applications. In this work, we have developed a novel integrated hydrodynamic model for simulating flash floods and debris flows. Overland flows, change of debris concentration and bed elevation change are simulated simultaneously to model the transition between flash flood and debris flow. The overland flow processes are simulated by solving the full SWEs using a Godunov-type finite volume method. A novel method for calculating erosion and deposition rates is incorporated into the SWEs-based model to simulate the change of debris concentration and bed elevation change. The new method can maintain numerical stability and accuracy even in the presence of vanishing velocity. Therefore, the new model can effectively simulate the full process of rainfall-runoff-flooding turning into debris flows. Satisfactory simulation results have been obtained for both laboratory-scale and real-world test cases. The new model has the potential to be applied for flash flood/debris flow risk assessment and early warning.. DOI: 10.5194/egusphere-egu23-5869.

Jiang, J and Liang, Q (2023) Evaluating the feasibility and performance of Nature-based Solutions in Can Tho, Vietnam, Can Tho, the largest city in the Mekong River Delta, is experiencing rapid urbanisation that is causing many typical urbanisation-related issues, including the increasing flood risk. The flooding area has expanded from 30% to 50% of the total city area due to urbanisation and climate change. Due to the low topography and poor capacity of drainage systems, the city may sometimes remain inundated for up to three hours after the rain event has ended. It is essential to develop effective and also sustainable management strategies for the city to mitigate risk of flooding, especially surface water flooding caused by extreme heavy rainfall.Nature-based Solutions (NbS) are proposed and widely promoted globally as a sustainable strategy for managing flood risk and creating other benefits. For flood risk management, NbS can help a city reduce surface runoff and subsequently release pressure on drainage systems through infiltration and interception, thus mitigating flood risk. Numerical modelling has been widely used to support the design and assessment of NbS. Conventionally, NbS modelling is achieved by integrating a hydrological model with NbS simulation modules though a one-way coupling method. Such models are incapable of fully describing the rainfall-runoff-flooding processes dynamically interacting with NbS measures, and therefore can only provide limited information such as temporal and spatial variation of runoff removal rate for NbS design and evaluation.In this work, a 2D hydrodynamic flood model is adopted and further developed by coupling with compatible NbS simulation approaches to overcome the existing NbS restrictions. The new modelling framework is applied in Can Tho city to evaluate the feasibility and performance of different NbS against various evaluating metrics. The simulation results indicate that green roofs, rain gardens, and bio-retention cells can effectively reduce inundation area, flow rate, and runoff volume to protect localised infrastructure and key buildings under certain rainfall scenarios. However, dramatic change of flow velocities is observed near the key infrastructure and structures following the implementation of a rain garden, posing higher risk to pedestrians and vehicles. In-depth analysis of the hydrological performance of bio-retention cells further indicates that their designed capacity is not sufficiently exploited due to the inappropriate installation location, further demonstrating the advantage of the proposed model for better planning and design of NbS to achieve optimised performance.. DOI: 10.5194/egusphere-egu23-8422.

Qin, H and Liang, Q (2023) Development of a Coupled Human And Natural Systems (CHANS) Modelling Approach for flood risk assessment and management, Keywords: CHANS modelling, inundation model, agent-based model, risk assessment, flood risk managementFlooding is the most wide-spreading natural hazard threatening people’s lives and properties worldwide. In recent years, rapid urbanisation and more frequent weather extremes have led to increased risk of flooding, evidenced by the costly summer floods occurred in Europe and China in July 2021 and, most recently, the deadly event affecting most areas across Pakistan. Effective flood risk management is essentially needed to protect people’s lives and properties.Human activities may significantly influence flooding processes and the subsequent risk. However, few flood risk assessment and management practices directly consider human activities and social dynamics. This study aims to develop a Coupled Human And Natural System (CHANS) model to simulate the human-nature interacting processes during a flood event, which is subsequently applied to assess flood impact and evaluate the effectiveness of different disaster management options. The CHANS modelling framework is implemented by coupling the in-house High-Performance Integrated hydrodynamic Modelling System (HiPIMS) and an agent-based model built on the Flexible Large-scale Agent Modelling Environment of the Graphics Processing Unit (FLAMEGPU). The agent-based model simulates the complex behaviours of individuals and households reacting to the dynamic flooding process predicted by HiPIMS. The new CHANS modelling framework is tested by simulating the household damage caused by the 2015 Desmond flood in the 2500 km2 Eden Catchment in England, and the simulation results are consistent with the data released in government reports. The model is further applied to explore the role of early warning and sandbagging in mitigating flood impacts. The validated CHANS flood risk modelling and assessment framework is further applied to the City of Can Tho in the Vietnamese Mekong Delta to assess compound flood risk taking into account dynamic household vulnerability and explore different risk mitigation measures.. DOI: 10.5194/egusphere-egu23-9446.

Xiong, Y, Liang, Q, Wang, G (2023) Modelling the Dynamics of Multiple Floating Vehicles Driven by Transient Flood Waves, Many post-event field investigations of water-related hazards suggest that debris-enriched flow is much more destructive than water flow alone. However, the role of floating objects is rarely considered in the modelling or risk assessment approaches in practice. Existing modelling approaches are mostly focused on a single or limited pieces of debris. The interactions between the flow and multiple floating objects are not well explored and understood, and few modelling tools have been developed with the capability to simulate and predict these complex interactive processes.This work aims to present a two-way coupling numerical model for simulating the full-process dynamics of floating debris driven by flood waves, based on a finite volume shock-capturing hydrodynamic model solving the 2D shallow water equations and a 3D discrete element method (DEM) model. A multi-sphere method (MSM) is introduced to the DEM model to better capture the shape and size of floating objects. The coupled model estimates the hydrostatic and dynamic forces acting on debris directly using the high-resolution water depth and velocity predicted by the hydrodynamic model, efficiently and automatically capturing the interactive dynamics between transient water flow and floating debris. The model is able to simulate the full-process dynamics of floating debris, including vertical displacement, initiation, horizontal transport, depositing, interaction with and impact on structures.After being validated against experiment tests, the model is applied to reproduce a flash flood event in the coastal village of Boscastle, UK, in 2004. During the event, over 100 vehicles were carried by extreme water flow, which blocked and damaged a couple of downstream bridges, changed the pathway and extent of flooding, and finally moved with the flood water to the river mouth. The coupled model well predicts the flood dynamics, transport processes of floating vehicles, and their final locations. Further numerical experiments are caried out to discover and understand the process of floating debris blocking a bridge and the transport process and spatial distribution of different number of floating vehicles during the flood event. This model potentially provides a new and robust tool to more realistically assess flash flood risk and inform planning and design or urban buildings and infrastructure.. DOI: 10.5194/egusphere-egu23-5931.

Tong, X, Liang, Q, Zhao, J (2023) A high-performance integrated hydrodynamic modelling framework for large-scale multi-process simulation, Coastal cities are prone to the risks from multiple hazards, e.g, compound floods driven simultaneously by interactive fluvial, pluvial and coastal processes. The overland flow and flooding process of a compound event may further erode soil, move and carry along debris of different size, and pick up and transport pollutants to create secondary hazards to exacerbate the flood impact on assets and environment. When assessing and managing multi-hazard risk, it is essential to have a modelling tool that can depict in detail the flooding and associated processes. However, the traditional flood models seldomly consider and simulate the interactive rainfall-runoff-flooding and associated secondary hazard processes.This work aims to develop and test a high-performance portable modelling framework to simulate the flooding dynamics triggered by multiple drivers, as well as the relevant cascading processes, to support more comprehensive multi-hazard risk assessment and management. To simulate the complex flooding dynamics from multiple sources, the High-Performance Integrated hydrodynamic Modelling System (HiPIMS) developed at Loughborough University is adopted. HiPIMS solves the full 2D shallow water equations (SWEs) using a Godunov-type finite volume method, implemented with novel variable reconstruction and source term discretisation schemes to handle complex domain topography and wetting and drying to achieve stable and accurate prediction. HiPIMS is further implemented on multiple GPUs to achieve high-performance computing to support large-scale high-resolution simulations. In this work, a new version of more compatible and portable HiPIMS is developed by adopting PyTorch (https://pytorch.org) to distribute GPU threads and reconstruct input data and internal variables, making it easier for interfacing with GIS tools and data pre- and post-processing. To ensure the new HiPIMS is extendable to incorporate new modelling components to achieve multi-hazard and multi-process modelling, the main model code is encapsulated to provide interfaces with easy access to hydrodynamic information, i.e, water depths and velocities, for model coupling. Git (a distributed version control system for programmers to collaboratively develop source codes) is further employed to support long-term flexible model development and maintenance.The capability of the new HiPIMS is demonstrated and confirmed by application to 1) reproduce a surface water flood event driven by fluvial and pluvial processes across the 2500km2 Eden catchment in England; 2) initiation and propagating process of floating debris driven by highly transient flood waves; and 3) wash-off, transport and deposition of non-point-source pollutants driven by rainfall induced overland and flood flows over urban surfaces.. DOI: 10.5194/egusphere-egu23-15113.

Guan, M, Liang, Q, Hou, J (2021) Editorial: Smart Approaches to Predict Urban Flooding: Current Advances and Challenges. DOI: 10.3389/feart.2021.681751.

Liang, Q (2019) Editorial. DOI: 10.1680/jwama.2019.172.1.1.