Droughts stand among the most damaging natural disasters in human, environmental and economic terms. Since 1900, more than 11 million people have died as a consequence of droughts and more than 2 billion have been affected by droughts. The severity of drought depends on its duration, intensity, spatial extent, and local socioeconomic conditions. According to the IPCC report, the duration and intensity of droughts have increased and the extent of drought-affected areas globally is likely to increase over the next century, which is broadly consistent with expected changes in the hydrologic cycle under warming. Therefore, drought monitoring and forecasting is vital for stakeholders (e.g., the government, local authorities, private sectors, communities, and farmers) to make decisions on drought management and mitigation. Droughts can be monitored effectively using climatic drought indices. But there is limited capability to use these indices due to sparse observation networks. Now, with the advent of advanced remote sensing techniques, a range of Big Data sources have been recognized as useful tools for the large-scale area monitoring. We believe that the advances in land surface models, global Big Data sources, and data assimilation now make it possible to develop a regional drought monitoring and forecasting system for drought-affected areas, where drought predictions are most needed and in situ networks are sparse. Therefore, this PhD project will deliver a better understanding of the drought impacts and support increased preparedness and resilience to droughts, and hence will contribute to societal well-being, environmental sustainability, and economic growth in the drought-affected areas.
We are seeking applications from graduates in a relevant subject area, such as hydrology, physical geography, and computing science. Graduates in mathematics, physics, and engineering with an interest in applying their skills to the environmental sciences are also welcome. This project requires strong numerical and analytical skills, and relevant programming experience.
Full studentships (UK/EU tuition fees and stipend £14,296) for UK/EU students for 3.5 years or full studentships (International tuition fees and stipend £14,057) for International students for 3 years. International applicants who possess suitable self-funding are also invited to apply.
In the first instance, please contact Dr Xiaogang Shi at[hidden email]to express your interest, supplying a CV and cover letter.