Revealing the Regolith: the Critical Role of the Subsurface in Co-Seismic Shallow Landsliding

Project Code: BOULTON_PLYM_ARIES27_CASE

Revealing the Regolith: the Critical Role of the Subsurface in Co-Seismic Shallow Landsliding

Project Code: BOULTON_PLYM_ARIES27_CASE

Project Description

Supervisors

Professor Sarah Boulton, School of Geography, Earth and Environmental Sciences, University of Plymouth – contact me

Dr Martin Stokes, SoGEES, University of Plymouth

Dr Suryodoy Ghoshal, SoGEES, University of Plymouth

 

Scientific Background

Shallow landslides (i.e., slope failures in surface material typically < 2 m thick) are a global hazard, posing significant risk to infrastructure and populations1 especially in seismically active regions. However, it is still not possible effectively predict the location of future landslides2. A significant factor in the occurrence of shallow landslides is the amount of material available to fail; the mobile soil layer above solid bedrock called regolith. Regolith controls the size and distribution of shallow landslides across unstable landscapes. Yet, global knowledge of the thickness and physical properties of this horizon is extremely rare.  Recent modelling3 using a novel landscape evolution model component and a co-seismic landslide inventory suggests a different approach – that regional regolith thickness can instead be inferred from databases of landslide occurrences using inverse modelling.

To unlock the potential of this novel approach, this PhD will utilise the dynamic landscape of the central Italian Apennines, an accessible and data rich area prone to landslides and earthquakes5, to test if the modelled regolith thicknesses correlate with field derived observations. This project addresses a fundamental knowledge gap, providing vital information to improve hazard modelling and mitigation strategies in vulnerable regions worldwide.

 

Research Methodology

The researcher will: 1) undertake ensemble modelling of shallow landslides using the ShallowLandslider3 Landlab component to generate and compare plausible subsurface regolith configurations; 2) assess spatial patterns of plausible landslides against a regional multi-temporal dataset to infer the best fit regolith characteristics; 3) undertake field data collection and follow-up laboratory analysis to constrain the regolith parameters and soil production rates across a number of key locations in the Central Apennines, and 4) test model outputs against field-constraints to improve landslide forecasting.

 

Training

The individual joins a team of international experts who will support through training in computer modelling and programming (Python/Matlab), remote sensing and GIS, field geomorphic techniques (geomorphic mapping, TruPulse, DGPS/drone surveys), geochemistry, engineering geology methodologies (slope stability, rock strength assessment) and transferable research skills.

 

Person Specification

We seek a candidate confident in undertaking fieldwork and data integration across geological disciplines. Prior experience of GIS/Remote sensing or programming is desirable.

Acceptable first degree subject(s): A degree in a geoscience discipline (e.g., geology, Earth sciences, physical geography, geophysics), GIS/Remote sensing or similar is desirable.

References

  • Froude, M.J. and Petley, D.N., 2018. Global fatal landslide occurrence from 2004 to 2016. Natural hazards and earth system sciences, 18(8), pp.2161-2181.
  • Jones, J. N., Boulton, S. J., Bennett, G. L., Stokes, M., & Whitworth, M. R. Z., 2021. Temporal Variations in Landslide Distributions Following Extreme Events: Implications for Landslide Susceptibility Modeling. Journal of Geophysical Research: Earth Surface, 126(7). doi:10.1029/2021jf006067
  • Ghoshal, S., Boulton, S.J., Hales, T.C., Bennett, G., Beswick, A., Jones, J.N., Lewin, S., Mildon, Z.K., Stokes, M., Whitworth, M.R. and Campforts, B., 2025. ShallowLandslider: a physics-based component for predicting regional distributions of coseismic landslides. EarthArXiv.
  • Jones, J.N., Boulton, S.J., Stokes, M., Bennett, G.L. and Whitworth, M.R., 2021. 30-year record of Himalaya mass-wasting reveals landscape perturbations by extreme events. Nature communications, 12(1), p.6701.
  • Atkinson, P.M. and Massari, R., 1998. Generalised linear modelling of susceptibility to landsliding in the central Apennines, Italy. Computers & Geosciences, 24(4), pp.373-385.

Key Information

  • This studentship has been shortlisted for funding under the UKRI NERC DLA funding scheme and will commence on 1 October 2027. The closing date for applications is 23:59 on 16 December 2026.
  • Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded studentship, which covers fees, maintenance stipend (£21,805 p.a. for 2026/27) and a research training and support grant (RTSG). A limited number of studentships are available for international applicants, with the difference between 'home' and 'international' fees being waived by the registering university. Please note, however, that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK, such as visa costs or the health surcharge.
  • ARIES postgraduate researchers (PGRs) benefit from bespoke training and ARIES provides £2,500 to every student for access to external training, travel and conferences, on top of all Research Costs associated with the project. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses. Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses.
  • ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside non-academic experience, and our recruitment process considers potential with the same weighting as past experience.
  • All ARIES studentships may be undertaken on a part-time or full-time basis. International applicants should check whether there are any conditions of visa or immigration permission that preclude part-time study. All advertised project proposals have been developed with consideration of a safe, inclusive and appropriate research and fieldwork environment with respect to protected characteristics. If you have any concerns, please contact us.
  • For further information, please contact the supervisor. To apply for this Studentship, follow the instructions at the bottom of the page or click the 'apply now' link.
  • ARIES is required by our funders to collect Equality and Diversity Information from all of our applicants. The information you provide will be used solely for monitoring and statistical purposes; it will remain confidential and will be stored on the UEA SharePoint server. Data will not be shared with those involved in making decisions on the award of Studentships and will have no influence on the success of your application. It will only be shared outside of this group in an anonymised and aggregated form. You will be asked to complete the form by the University to which you apply.
  • ARIES studentships are subject to UKRI terms and conditions. Postgraduate Researchers are expected to live within reasonable distance of their host organisation for the duration of their studentship. Please see https://www.ukri.org/publications/terms-and-conditions-for-training-funding/ for more information.

Apply Now

For further information on the application process for this studentship, please visit the  University of Plymouth's Research Degrees webpage.