Freddy Vinet

Flood frequency analysis using historical data: accounting for random and systematic errors.

Abstract Flood frequency analysis based on a set of systematic data and a set of historical floods is applied to several Mediterranean catchments. After identification and collection of data on historical floods, several hydraulic models were constructed to account for geomorphological changes. Recent and historical rating curves were constructed and applied to reconstruct flood discharge series, together with their uncertainty. This uncertainty stems from two types of error: (a) random errors related to the water-level readings; and (b) systematic errors related to over- or under-estimation of the rating curve. A Bayesian frequency analysis is performed to take both sources of uncertainty into account. It is shown that the uncertainty affecting discharges should be carefully evaluated and taken into account in the flood frequency analysis, as it can increase the quantiles confidence interval. The quantiles are found to be consistent with those obtained with empirical methods, for two out of four of the catchments. Citation Neppel, L., Renard, B., Lang, M., Ayral, P.-A., Coeur, D., Gaume, E., Jacob, N., Payrastre, O., Pobanz, K. & Vinet, F. (2010) Flood frequency analysis using historical data: accounting for random and systematic errors. Hydrol. Sci. J. 55(2), 192–208.

A comparative analysis of the loss of life during two recent floods in France: the sea surge caused by the storm Xynthia and the flash flood in Var

This paper aims to analyse and compare the loss of life that occurred during two recent floods in France. The first flood was due to a sea surge triggered by the storm called Xynthia that hit the Atlantic coast on 28 February 2010 (41 flood-related deaths). The second was a flash flood that struck the Var Department in the French Mediterranean region on 15 June 2010 (26 fatalities). After detailing the assumptions and expected outcomes of the study of disaster-related fatalities, the paper focuses on the characteristics of the victims and the circumstances of their deaths. In the first case, 71% of the victims were people aged over 60 (mainly women) who were surprised while they were sleeping and who died in or near their homes. In the case of the flash flood, the profiles of the victims were diverse as the flooding occurred in the afternoon and many people were trapped in open. The paper also highlights the factors that explain mortality. Physical factors such as water depth were determined. The relationship between the water depth and the age of victims was found to be relevant. In the case of the storm surge Xynthia, the correlation between age and water depth is positive. For the flash flood, the correlation between age and water depth was negative as male adults died in open. In the first case, the vulnerability of people was closely linked to human features such as type of housing and age that people are not directly responsible for. During flash floods, dangerous behaviour by people highlighted the role of risk-taking in loss of life. We also examined the particular case of the deaths of the children. The paper concludes by discussing the factors of vulnerability on frail population such as elderly people or marginalized. The lack of risk awareness and crisis preparedness were clearly a major factor of vulnerability.

14 – Assessing Vulnerability to Flooding: Progress and Limitations

Abstract: The geographical approach to risks has evolved over the last few decades. A “hazard-centered” process has given way to a more integrated approach, which takes in the social and territorial aspects of vulnerability. Vulnerability has conventionally been considered a component of risk but the scientific community still perceived it as only a minor part of the definition. However, the concept of vulnerability has evolved, become clearer and stabilized; more diagnostic methods have been developed on various scales. The limitations are due to the negative connotations of vulnerability, which often discourages risk managers (particularly elected representatives) from using it, and to the existence of a sort of “glass ceiling” that makes it impossible to entirely model vulnerability, fostering an image of methodological shortcomings compared with the “hard” sciences that govern risk assessment. Finally, the main challenge is still to use diagnostic methods to actually reduce risk.