Compound Drought & Groundwater Drought: Assessing Antecedent conditions on drought metrics

Project ID: 2228cd1384 (You will need this ID for your application)

UCL Lead department: Earth Sciences

Project Summary:

In the United Kingdom, future changes in climate are expected to alter the timing and amount of precipitation, changing the partitioning of terrestrial waters, including the volume of water that becomes groundwater recharge. A broad foundation of simulated effects between climate and groundwater have been built (cite), with improved insights about the physical processes that may regulate groundwater change. These models, however, do not capture the co-occurrence of different types of drought (e.g., meteorological, hydrological, agricultural) that can amplify groundwater drought, raising important questions about the future sustainability of groundwater resources. The propagation of drought, starting with precipitation deficits (meteorological drought) generate deficits in soil moisture (agricultural drought) and streamflow (hydrological drought), which in turn impact groundwater resources, potentially culminating in groundwater drought. The propagation of drought implies that different antecedent conditions in time and space regulate the severity and magnitude of drought. This concept, referred to as compound drought, provides a robust framework to assess potential future changes in groundwater resources.

In this project, you will explore changes in groundwater resources in the context of climate change and how these changes are connected to other aspects of terrestrial water storage. A key aspect of the work will be applying the compound drought framework to understand the role of antecedent drought conditions on the magnitude and severity of groundwater drought. The project will provide insight into the role of terrestrial water stores in evaluation of sustainability questions.

We are looking for a candidate with a keen interest in sustainability and groundwater resources, particularly with respect to water management. The ideal candidate will have strong kills in hydrology, data management, programming, and statistics. The candidate is expected to have an excellent academic track records with a STEM degree. We strongly encourage candidates from underrepresented backgrounds to apply.