Xilin Xia

School of Engineering

University of Birmingham

Birmingham, UK

Dr Xilin Xia is an assistant professor working on computational modelling of natural hazards and their impacts. His research interests cover computational hydraulics, high-performance computing, machine learning and their applications in modelling and understanding natural hazards such as flooding and landslides. His research vision is to develop advanced and holistic modelling technologies to facilitate the risk management of extreme weather induced hazards and enhance climate resilience.

Before joining Birmingham in May 2022, he lectured at Loughborough University and was a Research Associate at Newcastle University. He received his BEng and MEng from Wuhan University, China in 2010 and 2012, and his PhD from Newcastle University in 2017. He is also a Turing Fellow at The Alan Turing Institute since March 2024.

news

Mar 2, 2024	He has been appointed as a Turing Fellow at The Alan Turing Institute, starting from 1st March 2024.
Apr 2, 2022	He will take the position of Assistant Professor in Resilience Engineering at the University of Birmingham from 3 May.

selected publications

Landslides

Movement process analysis of the high-speed long-runout Shuicheng landslide over 3-D complex terrain using a depth-averaged numerical model

Zhao, Weihua, Xia, Xilin, Su, Xiaoli, Liang, Qiuhua, Liu, Xiuwei, and Ju, Nengpan

Landslides 2021

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Flow-like landslide is one of the most catastrophic types of natural hazards due to its high velocity and long travel distance. In 2019, a large catastrophic landslide was triggered by heavy rainfall and occurred in Shuicheng County, Guizhou, China. The Shuicheng landslide was characterized by a short slip time, high speed, and long sliding distance, causing significant damages to the downstream communities and properties. Depth-averaged models have been widely used to predict the velocity and runout distance of flow-like landslides. However, most of the existing depth-averaged models have various shortcomings for application in real-world simulations. In this study, a high-performance depth-averaged model taking into account the effects of topography-related vertical acceleration and centrifugal force was used to examine the influence of complex 3-D terrain on the landslide movement process. The simulation results were in satisfactory agreement with the field observations. This work reveals the landslide movement process at different stages, including acceleration, diversion, secondary acceleration, impact, and deposition. The maximum average velocity was predicted to be 35 m/s, with a local maximum velocity exceeding 50 m/s. The seismic records obtained from the adjacent seismic stations and the predicted kinetic energy and velocity of the landslide event revealed a dual acceleration and obstruction process. It was also found that the movement process and final deposit morphology were strongly influenced by the complex terrain and were sensitive to the surface friction coefficient. This may also be the reason for the survival of some houses in the middle of the slope during the event. This study provides a reference for investigating long-runout, high-speed, flow-like landslides.
ADWR

A full-scale fluvial flood modelling framework based on a high-performance integrated hydrodynamic modelling system (HiPIMS)

Xia, Xilin, Liang, Qiuhua, and Ming, Xiaodong

Advances in Water Resources 2019

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Full-scale fluvial flood modelling over large catchments has traditionally been carried out using coupled hydrological and hydraulic/hydrodynamic models. Such a traditional modelling approach is not well suited for the simulation of extreme floods induced by intense rainfall, which is usually featured with highly transient and dynamic rainfall-runoff and flooding process. This work aims to develop and demonstrate a modelling framework to predict the full-scale process of fluvial flooding from the source (rainfall) to impact (inundation) over a large catchment using a single high-performance hydrodynamic model driven by rainfall inputs. The modelling framework is applied to reproduce the flood event caused by the 2015 Storm Desmond in the 2500 km2 Eden Catchment at 5 m resolution. Without intensive model calibration, the predicted results compare well with field observations in terms of inundation extent and gauged water levels across the catchment. Sensitivity tests reveal that high-resolution grid is essential for accurate simulation of fluvial flood events using a 2D hydrodynamic model. Accelerated by multiple modern GPUs, the simulation is more than 2.5 times faster than real time although it involves 100 million computational cells inside the computational domain. This work provides a novel and promising approach to assess and forecast at real time the risk of extreme fluvial floods from intense rainfall.
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A new depth-averaged model for flow-like landslides over complex terrains with curvatures and steep slopes

Xia, Xilin, and Liang, Qiuhua

Engineering Geology Feb 2018

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Flow-like landslides are one of the most catastrophic types of natural hazards due to their high velocity and long travel distance. They travel like fluid after initiation and mainly fall into the ‘flow’ movement type in the updated Varnes classification (Hungr et al., 2014). In recent years, depth-averaged models have been widely reported to predict the velocity and run-out distance of flow-like landslides. However, most of the existing depth-averaged models present different shortcomings for application to real-world simulations. This paper presents a novel depth-averaged model featured with a set of new governing equations derived in a mathematically rigorous way based on the shallow flow assumption and Mohr-Coulomb rheology. Particularly, the new mathematical formulation takes into account the effects of vertical acceleration and curvature effects caused by complex terrain topographies. The model is derived on a global Cartesian coordinate system so that it is easy to apply in real-world applications. A Godunov-type finite volume method is implemented to numerically solve these new governing equations, together with a novel scheme proposed to discretise the friction source terms. The hydrostatic reconstruction approach is implemented and improved in the context of the new governing equations, providing well-balanced and non-negative numerical solutions for mass flows over complex domain topographies. The model is validated against several test cases, including a field-scale flow-like landslide. Satisfactory results are obtained, demonstrating the model’s improved simulation capability and potential for wider applications.
WRR

An efficient and stable hydrodynamic model with novel source term discretization schemes for overland flow and flood simulations

Xia, Xilin, Liang, Qiuhua, Ming, Xiaodong, Hou, Jingming, Lu, Xinhua, Mao, Bing, Dong, Bingjiang, Xia, Xilin, Liang, Qiuhua, Ming, Xiaodong, and Hou, Jingming

Water Resources Research May 2017

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Numerical models solving the full 2D shallow water equations (SWEs) have been increasingly used to simulate overland flows and better understand the transient flow dynamics of flash floods in a catchment. However, there still exists key challenges that have not yet been resolved for the development of fully dynamic overland flow models, related to 1) the difficulty of maintaining numerical stability and accuracy in the limit of disappearing water depth; and 2) inaccurate estimation of velocities and discharges on slopes as a result of strong nonlinearity of friction terms. This paper aims to tackle these key research challenges and present a new numerical scheme for accurately and efficiently modelling large-scale transient overland flows over complex terrains. The proposed scheme features a novel surface reconstruction method (SRM) to correctly compute slope source terms and maintain numerical stability at the small water depth condition, and a new implicit discretisation method to handle highly nonlinear friction terms. The resulting shallow water overland flow model is first validated against analytical and experimental test cases and then applied to simulate a hypothetic rainfall event on the 42 km2 Haltwhistle Burn, UK.