Effect of data trade-offs on flood risk modelled using high and low complexity hydrological models in a highly urbanized data-sparse coastal region

With Olumese Efeobokhan, University of Nottingham.

All seminars online. Please contact sue.davis@nottingham.ac.uk for the link. Subject to change.

Part of the Geosciences Seminar Series.

Abstract

An essential facilitator for plausible flood risk management (FRM) is the availability of reliable data for flood risk analysis which will in turn drive favourable flood risk policies. Unfortunately, this poses a big challenge in regions that lack reliable meteorological, topographic and land use data.

This research focuses on the conduct of flood modelling by manipulating limited data available using a simplified model, and comparing predicted flood risk with results obtained from a high performance, complex-data driven hydrological model. The emphasis of the research is on determining trade-offs in parameterizing flood models that can be used for flood risk modelling in areas that have limited meteorological and topographical data.