Information-gap analysis of flood model uncertainties and regional frequency analysis

Abstract

Flood risk analysis is subject to often severe uncertainties, which can potentially undermine flood management decisions. This paper explores the use of information gap theory to analyze the sensitivity of flood management decisions to uncertainties in flood inundation models and flood frequency analysis. Information gap is a quantified nonprobabilistic theory of robustness. To analyze uncertainties in flood modeling, an energy-bounded information gap model is established and applied first to a simplified uniform channel and then to a more realistic 2-D flood model. Information gap theory is then applied to the estimation of flood discharges using regional frequency analysis. The use of an information gap model is motivated by the notion that hydrologically similar sites are clustered in the space of their L moments. The information gap model is constructed around a parametric statistical flood frequency analysis, resulting in a hybrid model of uncertainty in which natural variability is handled statistically while epistemic uncertainties are represented in the information gap model. The analysis is demonstrated for sites in the Trent catchment, United Kingdom. The analysis is extended to address ungauged catchments, which, because of the attendant uncertainties in flood frequency analysis, are particularly appropriate for information gap analysis. Finally, the information gap model of flood frequency is combined with the treatment of hydraulic model uncertainties in an example of how both sources of uncertainty can be accounted for using information gap theory in a flood risk management decision.

Jim Hall

Professor of Climate and Environmental Risk

Prof. Jim Hall FREng is Professor of Climate and Environmental Risks in the University of Oxford and Director of Research in the School of Geography and the Environment.