Runoff responses to a changing climate in a dryland basin (NERC GW4+ DTP Projects 2018-19)

The aim of this project is to understand the responses of surface runoff generation in a dryland basin subject to climate change using a combination of modelling, fieldwork and data analysis. The project will employ the catchment hydrological model Dynamic Topmodel co-developed by supervisor Freer, to simulate runoff generation using a climate driver that enables the spatial and temporal variability of rainfall inputs. The STOchastic Rainstorm Model (STORM), developed by supervisors Singer and Michaelides, is a simple, flexible stochastic rainstorm generator, that is easy to apply and adapt to represent various classes of climate or climate change. The student will drive Dynamic Topmodel with STORM for a set of characteristic climatic forcings and expressions of climate change to explore runoff generation (discharge magnitude and frequency; and spatial patterns) within the basin over decadal timescales. The research will be based within the Walnut Gulch Experimental Watershed in beautiful SE Arizona, USA. This site has been well studied and instrumented for >60 years and contains world class datasets on rainfall, runoff, sediment flux, vegetation, and elevation. The student will take advantage of these datasets for testing and driving the models and will have the opportunity to spend time each year in Arizona for further data collection.