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Dr C Onof
No more applications being accepted
Funded PhD Project (European/UK Students Only)
About the Project
Hydrological simulation and design needs to take into account the projected changes as estimated by General and Regional Circulation Models (GCM/RCM). Much experience has been gained about how to use the reliable information produced by such models (pressure, mean sea-level pressure, ...) to generate in particular realistic time-series of rainfall at a number of sites over an area of interest (e.g. catchment). The Generalised Linear Model approach that is used for that purpose is not, however, adapted to the generation of finer-scale rainfall because of the complexity of the spatial structure of rainfall at those finer scales. For many hydrological applications, the daily time-scale is too coarse, so that another disaggregation tool is required to produce hourly and potentially sub-hourly rainfall series. This project will focus upon using point process models of rainfall at a single site to carry out this task. The idea will be to carry out the temporal downscaling at one site and use that information to downscale rainfall at the other sites so as to reproduce the observed hourly or sub-hourly spatial structure. One avenue of investigation will be whether information about storm advection can be inferred from an RCM. The project is closely linked to work currently carried out for Anglian Water and Black & Veatch, and interaction with the Grantham Institute on climatological issues is expected.
Computational skills and some basic statistical knowledge are required.
Computational skills and some basic statistical knowledge are required.
Funding Notes
NERC or EPSRC funding is available to provide PhD scholarships for suitably qualified eligible UK residents and EU citizens. Rules for funding eligibility can be found on the NERC (http://www.nerc.ac.uk/funding/ ) and EPSRC (http://www.epsrc.ac.uk/funding/Pages/default.aspx ) websites.
If you are interested in this studentship please send a covering email and CV to the relevant supervisor.
PLEASE NOTE: ALL APPLICATIONS RECEIVED ON OR BEFORE 16 APRIL WILL BE CONSIDERED, THEREAFTER APPLICATIONS WILL REMAIN OPEN UNTIL A SUITABLE CANDIDATE IS FOUND.
If you are interested in this studentship please send a covering email and CV to the relevant supervisor.
PLEASE NOTE: ALL APPLICATIONS RECEIVED ON OR BEFORE 16 APRIL WILL BE CONSIDERED, THEREAFTER APPLICATIONS WILL REMAIN OPEN UNTIL A SUITABLE CANDIDATE IS FOUND.
Project supervisors
Career overview
Dr Christian Onof completed his undergraduate studies in Mathematics and Engineering in Paris and Hanover. He undertook his PhD research at Imperial College London and began his academic career as a lecturer in 1994. His primary research area focuses on the stochastic modelling of rainfall fields for hydrological simulation and flood design, particularly at fine time-scales. Dr Onof has developed downscaling tools to assess the impact of climate change on hydrological variables and has recently explored the use of statistical and machine learning tools for forecasting convective rainfall. In addition to his research, Dr Onof has supervised several PhD students and his teaching emphasises Systems Engineering and Mathematical Modelling techniques. He has initiated new lecture courses in Statistics (MEng Year II), Operational Research (MEng Year IV), and Stochastic Hydrology (MSc). Dr Onof has lectured on over a dozen undergraduate papers and has taught a course in optimisation at the Ecole de Ponts Paris Tech as part of the European Athens Network. Dr Onof served as Course Director for an MSc course in Systems Engineering and Innovation and has been actively involved in promoting student exchange programmes between Imperial College London and various European universities. He has played a key role in establishing new exchange agreements with institutions such as the universities of Melbourne, Hong Kong PolyU, Barcelona, Queensland, and California.
Research interests
Dr Onof''s research primarily focuses on the stochastic modelling of rainfall fields aimed at hydrological simulation and flood design, particularly emphasising fine time-scales. He has developed downscaling tools to evaluate the impact of climate change on hydrological variables. Recently, he has been exploring the application of statistical and machine learning techniques for forecasting convective rainfall.
Stochastic Modelling
Rainfall Fields
Hydrological Simulation
Flood Design
Climate Change
Downscaling Tools
Statistical Tools
Machine Learning
Convective Rainfall
Systems Engineering
Mathematical Modelling
Statistics
Operational Research
Stochastic Hydrology
Environmental Engineering
Civil Engineering
Physical Geography
Atmospheric Sciences
Psychology
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