Professor Richard Ghail (Department of Earth Sciences, Royal Holloway, University of London)
During 2018-2019, earthquakes in Indonesia and Pakistan triggered deadly landslides that were both intimately connected to engineered water transport systems. At Palu, Sulawesi, lateral spreads were induced by liquefaction downslope of an irrigation conveyance canal during a September 2018 M7.5 earthquake. In September 2019, a M5.6 earthquake at Mipur, Azad Kashmir, caused rotational landslides along the banks of a canal downstream of the Mangla hydroelectric dam. Similar landslides in Iran and Tajikistan during the 20th Century highlight the risks associated with modifying natural water networks. Rapid development in tectonically-active countries is leading to unprecedented numbers of water engineering projects and associated urbanisation, often in areas with limited recent experience of large earthquakes.
This project aims to understand how water engineering projects affect the potential for earthquake-triggered landslides, especially in developing countries.
Stage 1: Collate known and suspected landslide examples.
Stage 2: Use remotely-sensed data, observations from selected field sites, targeted paleoseismic trenching, existing geotechnical information and earthquake parameters, detailed landslide studies to understand common features and the role of engineering projects in their development.
Stage 3: Analysis of historic and recent remote sensing data to compile a database of major water engineering projects in areas of high seismic risk. Stage 4: Numerical modelling, possibly supplemented by physical analogue models, to simulate future landslide style and probability and mitigation approaches.
Project-specific training will be provided in remote-sensing interpretation, image analysis, field-based geomorphology and paleoseismology, soil mechanics, landslide development and mitigation, alongside relevant GIS-based and modelling techniques.
The candidate will have a degree in a physical science, engineering or geography. They should be comfortable using GIS (geographic information systems) and/or MatLab or be a fast learner. A willingness to conduct fieldwork is important, as well as flexibility and adaptability. The project is impact-focused, aiming to contribute to a reduction in landslide vulnerability, so a desire to engage in delivering impact will be advantageous.