Developing risk-based approaches to modelling phosphorus contamination in agricultural catchments.
This project aims at developing a Decision Support Tool (DST) for tackling phosphorus pollution risk in Irish agricultural catchments. A high temporal and spatial resolution dataset including hydro-chemo-metrics, mapped soil properties and landscape characteristics, provided by the Agricultural Catchments Programme (Teagasc, IE), will serve as basis for the development of the tool. The DST will be built with a Bayesian approach, in collaboration with experts at The James Hutton Institute, Teagasc and the University of Reading. With this modelling approach, we hope to inform stakeholders and policy makers in building water quality mitigation strategies in high risk areas.
I hold a bachelor’s degree in Agricultural Sciences and Technologies from the University of Milan (Italy) and a master’s degree in Agro-Environmental Sciences (2017) also from the University of Milan. During my master I developed an interest in hydrology, thus my master thesis focussed on the evaluation of LiDAR data for improving a nutrient emission model developed at KU Leuven (Belgium). Prior to starting my PhD at the University of Reading I have had research experiences in China (China Agricultural University, Beijing) and Italy (University of Milan), in both cases focussing on environmental issues. I am also interested in scientific communication, in particular the communication of uncertainty; and closing the gender pay-gap.
- Water quality and quantity in agricultural catchments
- Bayesian approaches in environmental sciences