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.
Ramesh NI, Garthwaite AP, Onof C, 2018, A doubly stochastic rainfall model with exponentially decaying pulses, Stochastic Environmental Research and Risk Assessment, Vol:32, ISSN:1436-3240, Pages:1645-1664
et al., 2018, Censored rainfall modelling for estimation of fine-scale extremes, Hydrology and Earth System Sciences, Vol:22, ISSN:1027-5606, Pages:727-756
et al., 2018, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, Vol:556, ISSN:0022-1694, Pages:980-992
et al., 2018, Surface water flood warnings in England: overview, assessment and recommendations based on survey responses and workshops, Journal of Flood Risk Management, Vol:11, ISSN:1753-318X, Pages:S211-S221
et al., 2017, Let-It-Rain: a web application for stochastic point rainfall generation at ungaged basins and its applicability in runoff and flood modeling, Stochastic Environmental Research and Risk Assessment, Vol:31, ISSN:1436-3240, Pages:1023-1043