Miriam Cuba

email: m.cuba.1@research.gla.ac.uk

Research title: Understanding heavy-metal variation and extremes in the Glasgow Clyde River Basin using the G-BASE dataset

Research Summary

In the past, my research has been highly applied to the field of earth sciences. Some projects in hydrology included groundwater record interpolation and historical groundwater drought detection. In soil science, I worked on the prediction of crop yield, determining limiting factors in crop growth and yield, and identifying low-performing spatial regions within a field. Other projects included the prediction of electric network failure or supply-pipe bursts using precipitation and other weather variables. 

Currently, my PhD research centres around the adaptation of Extreme Value Theory to model the un-replicated extreme concentrations of heavy metal contaminants in the soil around the Glasgow Conurbation. The project adapts extreme value theory to the unreplicated spatial case to produce a measure for the probability of exceeding a given safety threshold. Other projects during my PhD have included modelling the probability of failure in wastewater treatment plants using weather variables as predictors. 



Marchant, B. P., Cuba, D., Brauns, B. and Bloomfield, J. P. (2022) Temporal interpolation of ground-
water level hydrographs for regional drought analysis using mixed models. Hydrogeology Journal
30(6), 1801–1817.

MacAllister, D.J., Krishan, G., Basharat, M. et al. A century of groundwater accumulation in Pakistan and northwest India. Nature  Geoscience. 15, 390–396 (2022). https://doi.org/10.1038/s41561-022-00926-1


Conference Proceedings

Brauns, B., Cuba, D., Bloomfield, J. P., Hannah, D. M., Jackson, C., Marchant, B. P., Heudorfer, B.,
Van Loon, A. F., Bessière, H., Thunholm, B. and Schubert, G. (2020) The Groundwater Drought
Initiative (GDI): Analysing and understanding groundwater drought across Europe. Proceedings of
the International Association of Hydrological Sciences 383, 297–305


External supervisors

Dr Benjamin Marchant (British Geological Survey) 



Cuba, M.D. 2022. Modelling Heavy Metal Soil Contaminant Dependence using Extreme Value Models. [Poster]. Royal Statistical Society International Conference 2022, 12-15 September, Aberdeen. 



Tutorials and Labs

Statistics for Biomedical Engineering


Inference (Level 3), Regression Modelling (Level 3), Advanced Bayesian Methods (Level M)


Tutorials and Labs

Inference, Linear Models, Design of Experiments (Level M), Generalized Linear Models (Level M)


Tutorials and Labs

Stochastic Processes (Level M), Biostatistics, Design of Experiments (Level M), Generalized Linear Models (Level M), Environmental Statistics (Level M).


Additional Information

Public Engagement

Committee member at the Young Statisticians Section (YSS) of the Royal Statistics Society since 2020. 



RET Associate Fellowship, awarded in 2022