Overview
Hydro-hazards, including floods, droughts, onshore and offshore landslides and storm surges, can pose direct threats to lives and impact livelihoods worldwide by damaging and destroying critical lifeline infrastructure (e.g. transport links, power supplies) as well as our natural ecosystem; especially under the changing climate. To mitigate risks and protect our towns, cities and our planet, we need to improve our understanding of the human-landscape-ecology interaction and characterise the complex hierarchies of revenant proves-response systems in a context of a changing and uncertain climate and environment. Inevitably, our human decision making and processes can also shape and change the natural environment, including ecosystems, river systems, vegetation and climate. We, humans, have caused such significant environmental change, which also has caused great concern about whether social and ecological systems can coexist in a sustainable manner. There is an urgent need to seek to understand how human activities can exist without disrupting the ability of natural ecosystems to function in order to help advance the concept of sustainability, and the interaction between natural hazards and human activities in order to minimize the disturbance to the onshore soil and submarine ecosystems, especially when we consider the next generation design of critical infrastructure (e.g. transport infrastructure). In particular, for example, plant root and shoot biomass – two important ecosystem attributes – are likely to influence the stability of hill slopes in complex ways. Although there is growing awareness of the benefits of ecosystem services for sustainable livelihoods in urban contexts, e.g. on the modification of climate, hydrology or soil dynamics, the potential for ecosystem-based and hybrid solutions that combine grey and green approaches has not been tapped fully yet. Therefore, several fundamental challenges exist in current research. All these recent challenges in the maintenance of the current lifeline infrastructure and design of the future lifeline infrastructure – so to be more resilient towards the changing climates and sustainable for future changes – have emphasized the need for an inter-disciplinary approach drawing upon knowledge at the interface between traditional civil engineering with geophysics, remote sensing and earth observations, engineering geology, hydrology, meteorology, data science, uncertainty quantification and ecology.
Figure 1: Fig. 1 e Broad Habitats in Marston Vale from the satellite derived Land Cover Map 2007 (Howard et al. 2013).
Host
University of WarwickTheme
- Climate and Environmental Sustainability
Supervisors
Project investigator
Dr Xueyu Geng, University of Warwick ([email protected])
Co-investigators
Nikhil Nedumpallile Vasu, BGS ([email protected])
How to apply
- Each host has a slightly different application process.
Find out how to apply for this studentship. - All applications must include the CENTA application form. Choose your application route
Methodology
Two modelling paradigms that attempt to encompass the complexity of response in the transport system and sub-systems when subject to hydro-hazard stressors will be embedded into the proposed programme: (1) functional resilience, and
(2) networked resilience. Functional resilience will describe the underpinning of normal and post-disaster dynamic behaviour, including the loss in functionality and recovery profiles.
Networked resilience will characterize propagation effects that arise from cascade failures, the interdependence between infrastructures as well as the links with the surrounding ecosystems. The project will couple functional and network resilience to create a holistic understanding of transport infrastructure resilience against hydro-hazards as well as how the ecosystem has been shaped by those man-made infrastructures especially after the natural disaster, harmonizing inter-disciplinary approaches in qualitative methods (e.g. social-economic impact), and quantitative analysis (e.g. model building and data science).
Training and skills
Students will be awarded CENTA2 Training Credits (CTCs) for participation in CENTA2-provided and ‘free choice’ external training. One CTC equates to 1⁄2 day session and students must accrue 100 CTCs across the three years of their PhD.
Training for the research will be delivered in a combination of network-wide and local activities. Local activities include combined summer training school within the related research areas by the funded projects, e.g. training courses on Remote sensing for earth observation; Advanced spatial database methods; Statistical learning theory and applications. Field trips and engagement with local industry partners will also be also provided as part of the training programme.
Partners and collaboration
The partners include existing links with the natural hazard partnership (consortium of 19 government departments and agencies, trading funds and public sector research establishments) which enables coordinated and coherent advice for the government and the resilience community. The NHP informs the national risk register and publishes a national-level multi-hazard daily assessment. There is also a strong connection with the UK Met Office through the daily hazard landslide assessment that BGS undertakes within the NHP framework.
Further details
If you wish to apply to the project, applications should include:
- A CENTA application form, downloadable from: CENTA application
- A CV with the names of at least two referees (preferably three and who can comment on your academic abilities)
- Submit your application and complete the host institution application process via:https://warwick.ac.uk/fac/sci/lifesci/study/pgr/studentships/nerccenta Please quote CENTA23_W17 when completing the application form.
Applications to be received by the end of the day on Wednesday 11th January 2023.
Possible timeline
Year 1
Conducting literature reviews, data mining and data fusion for the related datasets; develop the initial statistical data analysis method to understand the relationship between different multiscale data sources and influential factors, e.g. land-use/land-cover, topography, geology, weather data, traffic data
Year 2
Develop machine learning algorithms for deep learning analysis to forecast the transport system resilient under the changing climate through UKCP18 dataset integration.
Year 3
Develop a risk classification map to analyse the ecosystem resilience along the transport networks.
Further reading
- Alves, A., Sanchez, A., Gersonius, B. and Vojinovic, Z., (2021) ‘Selecting multi-functional green infrastructure to enhance resilience against urban floods’. In Water Security in Asia (pp. 429-441). Springer, Cham.
- Chopra, S.S., Dillon, T., Bilec, M.M. and Khanna, V., (2016) ‘A network-based framework for assessing infrastructure resilience: a case study of the London metro system’. Journal of The Royal Society Interface, 13(118), p.20160113.
- Davis, C.A., (2021). ‘Understanding functionality and operability for infrastructure system resilience’. Natural Hazards Review, 22(1), p.06020005
- Filippini, R. and Silva, A., (2014). A modeling framework for the resilience analysis of networked systems-of-systems based on functional dependencies. Reliability Engineering & System Safety, 125, pp.82-91.
- O’Sullivan, T.L., Kuziemsky, C.E., Toal-Sullivan, D. and Corneil, W., (2013). ‘Unraveling the complexities of disaster management: A framework for critical social infrastructure to promote population health and resilience’. Social Science & Medicine, 93, pp.238-246.
- Wang, S., Gu, X., Luan, S. and Zhao, M., (2021). Resilience analysis of interdependent critical infrastructure systems considering deep learning and network theory. International Journal of Critical Infrastructure Protection, 35, p.100459.
COVID-19
The proposed is computationally modelling based, which will be less likely to be impacted by changes in the normal work patterns caused by the respiratory and contact infection pandemic. If under any circumstance, the project needs to be carried out by working from home, as long as the essential modelling software can be remotely accessed through a secured network, there should not have any major impact on the proposed project’s progress.