The aim of this project is to quantify the links between the occurrence of debris flow and antecedent meteorological conditions in the Tien Shan Mountains, Central Asia. This will enable the development of an early warning system based on the data generated by the European Centre for Medium-Range Weather Forecasts (ECMWF).
The observed climatic warming, glacier retreat and permafrost melt in the Tien Shan Mountains has increased the frequency and spatial extent of debris flow and landslides. While the causes of such hazards have been investigated extensively in Europe and North America, few studies are available for Central Asia where they provide a substantial threat to human lives and infrastructure. This project will investigate the meteorological aspects of the rainfall-triggered debris flows and landslides that occur in the Central Asian mountains. It will determine the thresholds in temperature, precipitation, snowmelt, and soil moisture that leads to the formation of these events with an overall aim of developing an early warning system based on the ECMWF (European Centre for Medium-Range Weather Forecasts) weather forecast.
The project will utilise advanced methods of statistical analysis applied to the regional observational data sets, ERA5 reanalysis data and ECMWF forecasts. The application of the data to the complex terrain will require work with GIS and remote sensing products. Field work in the northern Tien Shan will be possible in collaboration with the Kazakhstan Institute of Geography and Water Safety and Kazakhstan State Agency for Mudflow Protection, a regional disaster risk-reduction agency. Communication of project findings to the stakeholders will be required.
A strong candidate will require a 2.1 degree and an MSc in environmental science, meteorology, physical geography, or a numerical discipline, excellent numerical skills and be able to conduct overseas fieldwork. While remaining with the scope of this project, applicants are invited to help shape a proposal to meet their specific interests and expertise.