Usefulness of historical information for flood frequency analyses: Developments based on a case study

Abstract

[1] This paper illustrates how historical information on floods can be retrieved in the a priori unfavourable case of small and sparsely populated catchments, and how this information can improve the estimation of flood discharge quantiles. It is based on the analysis of four small gauged rivers located in the south of France. Using various sources of archives, the flood discharges were estimated for past historical periods ranging from 100 to 200 years. The corresponding historical discharge series were then used in combination with the available systematic measurement series to evaluate peak discharge quantiles. The selected Bayesian Monte Carlo Markov Chain statistical inference approach provides credibility intervals for the estimated quantiles, the width of which reflects the information content of the data set used for the inference. The use of the historical data in the inference procedure leads to significant reductions of these credibility intervals, even if limitations in the content of historical inventories are introduced. A sensitivity analysis is conducted in the second part of the paper to evaluate to what extent these positive conclusions on the added value of historical data for flood frequency analysis can be extrapolated to other case studies. The influence of the number of historical floods documented (perception threshold) and of the level of knowledge of historical flood peak discharges is studied. The results are consistent with the previous works on the same issue and explain why these works led to apparently contradictory conclusions concerning the possible usefulness of historical data in flood frequency studies.Citation: Payrastre, O., E. Gaume, and H. Andrieu (2011), Usefulness of historical information for flood frequency analyses: Developments based on a case study, Water Resour. Res., 47, W08511,

Use of historical information in extreme-surge frequency estimation: the case of marine flooding on the La Rochelle site in France

“…In order to base our statistical inference on the right tail of the selected distribution, detection and treatment of outliers are key elements to an effective frequency estimation and risk analysis (Barnett and Lewis, 1998;Chebana et al, 2012). During the last 4 decades, several authors (Leese, 1973; US Water Resources Council Hydrology Committee (USWRC), 1982; Stedinger and Cohn, 1986;Condie, 1986;Jarrett, 1990;Salas et al, 1994;Ouarda et al, 1998;Hamdi, 2011;Payrastre et al, 2011Payrastre et al, , 2013 have recognized the value of using other sources of information in the frequency estimation of extreme events.…”

“…HI are often imprecise, and we should consider their inaccuracy in the analysis. However, even with important uncertainty, the use of HI is a viable mean to decrease the influence of outliers by increasing their representativeness in the sample (Hosking and Wallis, 1986a;Wang, 1990;Salas et al, 1994;Payrastre et al, 2011).…”

How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France)

“…In our study, we have no prior information about GPD parameters for our data set. Consequently, we use a non-informative flat prior (f (θ) ∝ 1) (Payrastre et al, 2011). In that case, f (θ|D) is proportional to the likelihood function.…”

La méthode SHYREG débit—application sur 1605 bassins versants en France métropolitaine

“…La prise en compte de cette information supplémentaire dans l'estimation des paramètres d'une loi statistique (p.ex. loi GEV) permet de réduire les incertitudes sur l'estimation des quantiles rares (Naulet et al 2005, Neppel et al 2011, Payrastre et al 2011.…”