I am a Lecturer at Loughborough University and my research focuses on understanding and predicting changes in floods and fluvial systems in the context of contemporary shifts in climate, agricultural practices and urbanisation. My approach is statistical and computational; I use a combination of climatic and land cover information to disentangle the different drivers of flooding and fluvial change across a variety of climates and land use types. Using ensemble global climate model outputs I also develop probabilistic streamflow forecasts over a range of timescales to assess how floods and fluvial systems may change over time. I have a keen interest in data science and in developing new, interdisciplinary methods for understanding and projecting fluvial and hydro-climatic change.
Two new NERC-funded PhD positions starting in 2018 are available with me and colleagues at Loughborough University, as part of the CENTA Doctoral Training Programme.
Applications for 2018 entry are now live. Further details on how to apply can be found here. Please see the links above for further details. The application deadline is 22 January 2018.
Looking forward to presenting my research at the Oxford Water Network seminar series! More details here.
On October 12th, I will be giving a talk at Maynooth university on ‘Disentangling streamflow drivers and forecasting water hazards using Earth Observation’ (details here).
Two papers accepted this month:
Slater, L.J., Villarini, G. (2017) Evaluating the drivers of seasonal streamflow rates in the U.S. Midwest, Water (MDPI). Open Access. PDF.
Villarini, G., Slater, L.J. (In press) Examination of Changes in Annual Maximum Gage Height in the Continental United States Using Quantile Regression, Journal of Hydrologic Engineering (ASCE)
Delighted to have been appointed to the British Society for Geomorphology‘s Executive Committee as Outreach Secretary.
Our paper has just been accepted in Journal of Climate (American Meteorological Society)!
Zhang, W., Villarini, G., Slater, L., Vecchi, G.A., Bradley, A.A. (2017), Improved ENSO Forecasting using Bayesian Updating and the North American Multi Model Ensemble (NMME), Journal of Climate