After completing his undergraduate studies in Mathematics and Engineering in Paris and Hanover, Dr Onof undertook his PhD research at Imperial, and started as a lecturer in 1992. His main area of current research is in the stochastic modelling of rainfall fields for the purpose of hydrological simulation and flood design, with a particular emphasis upon fine time-scales. One particular focus of his research has been the development of downscaling tools which can be applied to assess the impact of climate change upon hydrological variables.
Dr Onof has supervised several PhD students. His teaching focuses upon Systems Engineering and Mathematical Modelling techniques. He has intitated new lecture courses in Statistics (MEng Year II), Operational Research (MEng Year IV), and Stochastic Hydrology (MSc). He has lectured in over a dozen undergraduate papers, and also taught a course in optimisation at the Ecole de Ponts Paris Tech as part of the European Athens Network.
Dr Onof is Course Director of a new MSc course in Systems Engineering and Innovation.
Dr Onof has been active in promoting student exchange programmes between Imperial and other universities in Europe, and been instrumental in setting up new exchanges with the universities of Melbourne, Hong Kong PolyU, Barcelona, Queensland, and California.
Cross D, Onof C, Winter H, 2020, Ensemble estimation of future rainfall extremes with temperature dependent censored simulation, Advances in Water Resources, Vol:136, ISSN:0309-1708, Pages:1-21
et al., 2019, A review of radar‐rain gauge data merging methods and their potential for urban hydrological applications, Water Resources Research, Vol:55, ISSN:0043-1397, Pages:6356-6391
Onof C, 2019, Reality in-itself and the Ground of Causality, Kantian Review, Vol:24, ISSN:1369-4154, Pages:197-222
Park J, Onof C, Kim D, 2019, A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales, Hydrology and Earth System Sciences, Vol:23, ISSN:1027-5606, Pages:989-1014
et al., 2019, Characterising intermittent water systems in data-scarce settings using a citizen science approach, 17th International Computing and Control for the Water Industry (CCWI) Conference, Exeter, UK