Emma Ford

Emma Ford is a final year PhD researcher at the University of Oxford, based at Hertford College, and a Stipendiary Lecturer at St Peter’s College, where she teaches undergraduate physical geography.

Her research sits at the intersection of hydrology, hydro-meteorology, machine learning, and explainable artificial intelligence. She works in large-sample hydrology, with a focus on improving both the prediction and physical understanding of hydrological extremes, particularly floods.

Emma is interested in how modern data-driven methods can be used not only to forecast extreme events more accurately, but also to identify the processes that models learn and represent. She examines how catchment characteristics, antecedent wetness, climate variability, rainfall structure, snow processes, and event sequencing interact to generate high-flow events across different landscapes and time periods.

She also collaborates with the UK Centre for Ecology & Hydrology and the Hydro-JULES team to investigate how climate variability shapes river flow regimes across large samples of catchments. She contributes LSTM-based flood analyses to national model intercomparison projects, helping evaluate how different modelling approaches represent high-flow extremes and hydrological variability.

A central aim of the research is to build large-sample models that are accurate, interpretable, and scientifically meaningful, so that machine learning can contribute to both prediction and understanding. This perspective is shaped by her background in Civil Engineering, experience in the UK water industry, training through Oxford’s MSc in Water Science, Policy and Management course, and the research network she has developed throughout her PhD.