CONTEXT / BACKGROUND: High mountainous areas all over the world are highly prone to multiple hazards, including interacting landslides and flooding, which cascade across national borders, affecting critical economic infrastructure and human settlements. While global warming appears to be exacerbating landslide risks in the form of glacier melting and permafrost thawing at high altitudes its future impact is not fully understood yet. For example, large-scale impacts from heat waves, ice loss and permafrost thawing at high elevations on landslide and flood risks for downstream populations need to be better understood, but are likely to be exacerbated because alpine areas may lose up to ~90% of its glaciers by 2100 in future climate change scenarios. A combination of regional scale observation using recent advances in Earth Observation with local scale validation of satellite observations and advanced data analytics appears to be needed for tackling this problem.
AIMS: Using satellite-based data, the project will aim to develop approaches for early detection of precursory signs of activity to alert of imminent landslide and associated flood risks including glacial lake outburst floods, landslide-induced tsunami, and associated changes to water courses. The specific objectives are: (a) Characterising ground deformation over rock slopes and morainic dams surrounding glacial lakes, watercourse and glacial lake area changes over time and patterns of glacial retreat that lead to lake formation; (b) Assess long-term changes to ice-cover and permafrost at high elevations exacerbated by climate change, focusing on impacts on landslide and flood risk over the past decade (for which EO data are available), including the risk of Glacial Lake Outburst Floods (GLOFs) and cascading mega-tsunami risk from landsliding into such lakes; (c) assess how risks from landslides and associated floods are likely to change using local IPCC climate forecasts.
METHODS: The proposed methods will involve use of past and current Earth Observation (EO) data on glacier ice changes to assess long-term dynamics to ice-cover and permafrost in high-elevation areas and impacts on landslide and flood risk. EO data will be used to assess the risk of Glacial Lake Outburst Flood (GLOF) hazards and landslides, using both repeat Synthetic Aperture Radar Interferometry (InSAR) and optical imagery from the Sentinel missions from the past decade to map ground deformation over morainic dams and slopes, and also to map glacial lake area development over time. Using approaches developed from past EO data, to develop approaches to detect where remote-region lakes form and grow in real time, forward-predicting extreme events such as GLOFs. Findings will inform assessments of increased landslide and flood risk downstream. Future climate scenarios from IPCC will be used to model how these risks are likely to change in future as a result of climate change impacts on glacier mass and permafrost area upstream.
FIELD DATA (ground truth validation): The student will likely be collecting data in the field to validate their satellite datasets, in close collaboration with the CASE partner in Switzerland (Center for Research on the Alpine Environment – CREALP) providing expertise in landslide risk management, logistical support during fieldwork and complementary information on environmental conditions. Fieldwork include the use of UAV flights over areas that were narrowed down using satellite EO to monitor ground deformation together with outcrop-based description of rock mass behaviour. This project will benefit from extensive fieldwork experience in the region from local partners in the Swiss Alps (CREALP) and the valuable fieldwork experience in high mountain region from colleagues at the British Antarctic Survey (BAS). The student will be invited to undertake a three months placement at CREALP-Switzerland during years 2 or 3.
CANDIDATE: We are looking for an excellent candidate with background education in geophysical sciences or wider geosciences education with strong background in quantitative skills (computing, Earth Observation, GIS, etc.). Applicants with background education in applied physics, computer science, engineering geology, etc. with interest in geohazards will also be welcomed.
This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See http://www.eo-cdt.org
'This 3 year 9 month long NERC SENSE CDT award will provide tuition fees (£4,500 for 2019/20), tax-free stipend at the UK research council rate (£15,009 for 2019/20), and a research training and support grant to support national and international conference travel. View Website