Use of historical data in flood‐frequency analysis

Benson, Manuel A.

doi:10.1029/tr031i003p00419

Cited by 64 publications

(26 citation statements)

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“…The use of historical floods for FFA has been more frequent since pioneer publications by Benson (1950) and Leese (1973) incorporating non-systematic (historical) data together with gauge records. Documentary data are particularly valuable where there is an account of all floods exceeding a certain stage (threshold), or censured level, over a long period prior the instrumental gauging (Fig.…”

Section: Flood Frequency Analysismentioning

confidence: 99%

Quantitative historical hydrology in Europe

Benito

Brázdil

Herget

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. In recent decades, the quantification of flood hydrological characteristics (peak discharge, hydrograph shape, and runoff volume) from documentary evidence has gained scientific recognition as a method to lengthen flood records of rare and extreme events. This paper describes the methodological evolution of quantitative historical hydrology under the influence of developments in hydraulics and statistics. In the 19th century, discharge calculations based on flood marks were the only source of hydrological data for engineering design, but were later left aside in favour of systematic gauge records and conventional hydrological procedures. In the last two decades, there has been growing scientific and public interest in understanding long-term patterns of rare floods, in maintaining the flood heritage and memory of extremes, and developing methods for deterministic and statistical application to different scientific and engineering problems. A compilation of 46 case studies across Europe with reconstructed discharges demonstrates that (1) in most cases present flood magnitudes are not unusual within the context of the last millennium, although recent floods may exceed past floods in some temperate European rivers (e.g. the Vltava and Po rivers); (2) the frequency of extreme floods has decreased since the 1950s, although some rivers (e.g. the Gardon and Ouse rivers) show a reactivation of rare events over the last two decades. There is a great potential for gaining understanding of individual extreme events based on a combined multiproxy approach (palaeoflood and documentary records) providing high-resolution time flood series and their environmental and climatic changes; and for developing non-systematic and non-stationary statistical models based on relations of past floods with external and internal covariates under natural low-frequency climate variability.

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Section: Flood Frequency Analysismentioning

confidence: 99%

Quantitative historical hydrology in Europe

Benito

Brázdil

Herget

et al. 2015

Hydrol. Earth Syst. Sci.

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“…COOK (1987) a indiqué que l'erreur dans le calcul des pointes de crues associées à des événe-ments récents, et dans des conditions idéales, sont de l'ordre de 10-25 %, et que ces erreurs sont largement plus importantes dans le cas des crues historiques. BENSON (1950) et HIRSCH (1987 ont souligné que les formules standard de probabilités empiriques (plotting position) ne sont pas applicables dans des analyses fréquentielles des crues incluant à la fois des données historiques et des données observées, BERNIER et al (1987) ont présenté une nouvelle méthode de détermination des probabilités empiriques des données historiques qui est cohé-rente avec le modèle de censure, HIRSCH (1987) a souligné que la longueur « réelle » de la période d'information historique n'est pas connue et est générale-ment censée débuter à la date de la première crue documentée (tel qu'adopté par BENSON, 1950et ZHANG, 1982. Cependant, cette période pourrait être plus longue car il existe généralement une période de durée non connue précédant cet événement au cours de laquelle aucune crue importante n'a eu lieu.…”

Section: Effet Des Incertitudes Des éVénements Historiquesunclassified

Utilisation de l'information historique en analyse hydrologique fréquentielle

Ouarda¹,

Rasmussen²,

Bobée³

et al. 2005

rseau

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L'utilisation de l'information historique dans une analyse fréquentielle permet de mieux mobiliser l'information réellement disponible et devrait donc permettre d'améliorer l'estimation des quantiles de grande période de retour. Par information historique, on entend ici de l'information relative à des grandes crues qui se sont produites avant le début de la période de mesure (dite période de jaugeage systématique) des niveaux et débits des lacs et rivières. On observe de manière générale que l'utilisation de l'information historique conduit à une diminution de l'impact des valeurs singulières dans les séries d'enregistrements systématiques et à une diminution de l'écart-type des estimations. Dans le présent article on présente les méthodes statistiques qui permettent la modélisation de l'information historique.Use of information about historical floods, i.e. extreme floods that occurred prior to systematic gauging, can often substantially improve the precision of flood quantile estimates. Such information can be retrieved from archives, newspapers, interviews with local residents, or by use of paleohydrologic and dendohydrologic traces. Various statistical techniques for incorporating historical information into frequency analyses are discussed in this review paper. The basic hypothesis in the statistical modeling of historical information is that a certain perception water level exists and that during a given historical period preceding the period of gauging, all exceedances of this level have been recorded, be it in newpapers, in people's memory, or trough traces in the catchment such as sediment deposits or traces on trees. No information is available on floods that did not exceed the perception threshold. It is further assumed that a period of systematic gauging is available. Figure 1 illustrates this situation. The U.S. Water Resources Council (1982) recommended the use of the method of adjusted moments for fitting the log Pearson type III distribution. A weighting factor is applied to the data below the threshold observed during the gauged period to account for the missing data below the threshold in the historical period. Several studies have pointed out that the method of adjusted moments is inefficient. Maximum likelihood estimators based on partially censored data have been shown to be much more efficient and to provide a practical framework for incorporating imprecise and categorical data. Unfortunately, for some of the most common 3-parameter distributions used in hydrology, the maximum likelihood method poses numerical problems. Recently, some authors have proposed use of the method of expected moments, a variant of the method of adjusted moments which gives less weight to observations below the threshold. According to preliminary studies, estimators based on expected moments are almost ...

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“…EFFECT OF HISTORICAL DATA Large historical floods have been taken into account in graphical estimation (Benson, 1950;NERC, 1975) and when so used they have an effect on the form of the distribution obtained implicitly on the graph paper. Inclusion of large historical floods and exclusion of smaller unobserved historical floods may introduce bias in the shape of the distribution so obtained.…”

Section: Effect Of Outliersmentioning

confidence: 99%

Factors affecting choice of distribution for flood series

Cunnane

1985

Hydrological Sciences Journal

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Rival candidate distributions for modelling flood series may give markedly different magnitudereturn period (Q-T) relationships, particularly at high T, A priori theoretical arguments, empirical criteria for distribution choice and previously used methods of discrimination between candidate distributions are discussed. The effects which method of parameter estimation, treatment of outliers, inclusion of large historical flood values, data transformations and causal composition of the flood population may have on choice of distribution are also considered,

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Use of historical data in flood‐frequency analysis

Cited by 64 publications

References 0 publications

Quantitative historical hydrology in Europe

Quantitative historical hydrology in Europe

Utilisation de l'information historique en analyse hydrologique fréquentielle

Factors affecting choice of distribution for flood series

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