Imperial College London

Dr Nataliya Le Vine (née Bulygina)

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Honorary Research Fellow



+44 (0)20 7594 6019n.le-vine CV




Miss Judith Barritt +44 (0)20 7594 5967




405Skempton BuildingSouth Kensington Campus





Nataliya graduated from Kharkov National University (Ukraine) with a Masters degree in Applied Mathematics. Then she came to the University of Arizona (USA) to pursue her PhD study in Hydrology and Water Resources, focusing on Bayesian mathematical structure estimation for hydrological models.

She joined Imperial College in 2008 as a post-doctoral researcher at the department of Civil and Environmental Engineering. Her research was funded under Flood Risks from Extreme Events program (NERC), Flood Risk Management  Research Consortium programme (EPSRC), and Changing Water Cycle programme (NERC). Nataliya was appointed as a lecturer at the department in 2013.

Her research interests include:

Bayesian prediction uncertainty estimation and reduction, model identification and correction, treatment of model structural error, integrated hydrological modelling, prediction for ungauged/ non-stationary basins

Selected Publications

Journal Articles

Bulygina N, Ballard C, McIntyre N, et al., 2012, Integrating different types of information into hydrological model parameter estimation: application to ungauged catchments and land use change scenario analysis, Wrr

Bulygina N, McIntyre N, Wheater H, 2011, Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes, Water Resources Research, Vol:47, ISSN:0043-1397

Bulygina N, Gupta H, 2011, Correcting the Mathematical Structure of a Hydrological Model via BayesianData Assimilation, Water Resources Research

Bulygina N, Gupta H, 2010, How Bayesian Data Assimilation can be used to estimate mathematical structure of a model, Serra, Vol:477

Bulygina N, Gupta H, 2009, Estimating the uncertain mathematical structure of a water balance model via Bayesian data assimilation, Water Resources Research, Vol:45, ISSN:0043-1397

Bulygina N, McIntyre N, Wheater H, 2009, Conditioning rainfall-runoff model parameters for ungauged catchments and land management impacts analysis, Hess, Vol:13, Pages:893-904

More Publications