Dr Lu Zhuo
Department of Civil and Structural Engineering
+44 114 222 5780
Full contact details
Department of Civil and Structural Engineering
Sir Frederick Mappin Building
My work aims to understand how large infrastructure networks in cities will react in the event of extreme hydrometeorological events.
DR LU ZHUO
Lu is originally from a small town in mainland China. She studied her MEng Civil Engineering (2011) and PhD (2016) in Hydrology and Satellite Remote Sensing at the University of Bristol. She then took up a postdoc position at Bristol to co-create and coordinate a Newton Fund; ‘Resilient Economy and Society by Integrated SysTems’ modelling project. The project aimed to address the earthquake- induced multi-hazards risk management issues in China, and incorporated a multidisciplinary team of natural scientists, engineers, and social scientists.
Lu’s research focusses on multi-hazard disaster risk management and system modelling. This incorporates multi-disciplinary knowledge into a dynamic and unified modelling framework to increase the resilience of cities against extreme hydrometeorological events (such as floods and landslides) caused by changing climates. Lu aims to numerically model the impact of these hazards on infrastructure networks, on people and on possible rescue and mitigation efforts. She helped with the development of HazardCM, which is unique software that assesses and numerically models cities and their resilience to natural hazards such as flooding.
- Research interests
Lu’s work covers:
- Agent-based city modelling on spatio-temporal dynamic hazard risk assessment and management.
- Climate change induced extreme hydrometeorological events modelling (flood, landslide, drought).
- Satellite remote sensing of Earth observations (soil moisture, rainfall, land cover, surface temperature), retrieval, optimisation.
- Scenario-based resilient and sustainable decision-making supports.
- Mesoscale Numerical Weather Prediction modelling (WRF).
- A hazard-human coupled model (HazardCM) to assess city dynamic exposure to rainfall-triggered natural hazards. Environmental Modelling and Software, 127. View this article in WRRO
- Application of hydrological model simulations in landslide predictions. Landslides. View this article in WRRO
- Estimation of soil moisture using modified antecedent precipitation index with application in landslide predictions. Landslides, 16(12), 2381-2393.
- Assessment of simulated soil moisture from WRF Noah, Noah-MP, and CLM land surface schemes for landslide hazard application. Hydrology and Earth System Sciences, 23(10), 4199-4218. View this article in WRRO
- Modeling the high-resolution dynamic exposure to flooding in a city region. Hydrology and Earth System Sciences, 23(8), 3353-3372. View this article in WRRO
- Relationship between rainfall variability and the predictability of radar rainfall nowcasting models. Atmosphere, 10(8). View this article in WRRO
- Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds. Journal of Hydrology, 574, 276-287.
- Evaluation of remotely sensed soil moisture for landslide hazard assessment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(1), 162-173. View this article in WRRO
- Exploration of empirical relationship between surface soil temperature and surface soil moisture over two catchments of contrasting climates and land covers. Arabian Journal of Geosciences, 10. View this article in WRRO
- Multi-source hydrological soil moisture state estimation using data fusion optimisation. Hydrology and Earth System Sciences, 21(7), 3267-3285. View this article in WRRO
- A scheme for rain gauge network design based on remotely sensed rainfall measurements. Journal of Hydrometeorology, 18(2), 363-379. View this article in WRRO
- Hydrological evaluation of satellite soil moisture data in two basins of different climate and vegetation density conditions. Advances in Meteorology, 2017, 1-15. View this article in WRRO
- Soil moisture deficit estimation using satellite multi-angle brightness temperature. Journal of Hydrology, 539, 392-405. View this article in WRRO
- Error distribution modelling of satellite soil moisture measurements for hydrological applications. Hydrological Processes, 30(13), 2223-2236.
- Satellite radiance assimilation using a 3DVAR assimilation system for hurricane Sandy forecasts. Natural Hazards, 82(2), 845-855.
- Could operational hydrological models be made compatible with satellite soil moisture observations?. Hydrological Processes, 30(10), 1637-1648.
- Misrepresentation and amendment of soil moisture in conceptual hydrological modelling. Journal of Hydrology, 535, 637-651. View this article in WRRO
- Seasonal ensemble generator for radar rainfall using copula and autoregressive model. Stochastic Environmental Research and Risk Assessment, 30(1), 27-38.
- Impact of complexity of radar rainfall uncertainty model on flow simulation. Atmospheric Research, 161-162, 93-101.
- An introduction to factor analysis for radio frequency interference detection on satellite observations. Meteorological Applications, 22(3), 436-443.
- Meta-analysis of flow modeling performances-to build a matching system between catchment complexity and model types. Hydrological Processes, 29(11), 2463-2477.
- Rain Rate Retrieval Algorithm for Conical-Scanning Microwave Imagers Aided by Random Forest, RReliefF, and Multivariate Adaptive Regression Splines (RAMARS). IEEE Sensors Journal, 15(4), 2186-2193.
- Radar rainfall uncertainty modelling influenced by wind. Hydrological Processes, 29(7), 1704-1716.
- Adjustment of wind-drift effect for real-time systematic error correction in radar rainfall data. Physics and Chemistry of the Earth, Parts A/B/C, 83-84, 178-186.
- Evaluation of SMOS soil moisture retrievals over the central United States for hydro-meteorological application. Physics and Chemistry of the Earth, Parts A/B/C, 83-84, 146-155.
- Appraisal of NLDAS-2 Multi-Model Simulated Soil Moistures for Hydrological Modelling. Water Resources Management, 29(10), 3503-3517.
- Antecedent wetness and rainfall information in landslide threshold definition.
- Soil moisture sensor network design for hydrological applications. Hydrology and Earth System Sciences, 24(5), 2577-2591. View this article in WRRO
- Research group
Resources, Infrastructure Systems and built Environments Discipline
SuDS (Sustainable Drainage Systems) and Urban Drainage
Catchments and River Engineering
- Professional activities
- Engineering Faculty Commendation for Best PhD Thesis (University of Bristol)
- Conference convenor in session “Increasing Resilience to Natural Hazards in Earthquake Prone Regions in China (IRNHiC)” at the 2017 EGU
- Published over 30+ peer-reviewed journal and conference papers including in high impact journals such as Hydrology and Earth System Sciences and Journal of Hydrology
- Reviewer for top-tier journals, including Journal of Hydrology, Hydrological Processes, Remote Sensing, Atmospheric Research, Hydrological Science Journal, and Hydrology Research
- Potential PhD offerings
This PhD project will focus on the integration of the hydrodynamic model, traffic model, and urban Digital Twin for extreme flooding risk assessment, and management, in particular,
- the simulation of flood events based on different climate change scenarios
- enhance the performance of the hydrodynamic model through model modifications and coupling technologies.
- the integration of the hydrodynamic model, traffic model and the city Digital Twin
- urban flood risk assessment on traffic networks
- study on resilience and sustainable decision-making supports for future urban planning and development
This PhD project will focus on further developing a dynamic disaster risk assessment tool called HazardCM, which is an agent-based model that can simulate the dynamic human exposure to natural hazards. In particular, the project is to add -
- an infrastructure network module to cover a wide range of lifeline criticalities such as road, water, energy, bridges, etc;
- a hazard mitigation module to assess the effectiveness of different mitigation measure options;
- a resilience module to estimate the key social impact factors such as vulnerability and risks.
This PhD project will particularly focus on modelling the multi-hydrometeorological hazards (floods, landslides and debris flow) and provide useful research outcomes (e.g., multi-hazard risk maps) for hazard risk management. Satellite remote sensing technology will also be adopted to build a multi-hazard inventory map.