On seasonal approach to flood frequency modelling. Part II: flood frequency analysis of Polish rivers

Kochanek, Krzysztof; Strupczewski, Witold G.; Bogdanowicz, Ewa

doi:10.1002/hyp.8178

Cited by 32 publications

(29 citation statements)

References 17 publications

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“…As it was expected for the given season separation, it can be seen that the annual distribution is similar to that of the dominant flood season Kochanek et al, 2012). This can be explained by noticing that the majority of the annual maxima occurs during the flood season (i.e.…”

Section: Estimation Of Seasonal and Annual Flood Frequency Distributionssupporting

confidence: 69%

“…It is also significant to note that season identification based on climatic behaviours, rather than an arbitrary selection, leads to yearly subperiods that are well distinguished from a climatic point of view and therefore are more likely to be independent (e.g. Waylen and Woo, 1982;Durrans et al, 2003;Kochanek et al, 2012). Table 1 reports the results of the Plotting Position Correlation Coefficient (PPCC) test (e.g.…”

Section: Season Identificationmentioning

confidence: 99%

“…For instance, Stedinger et al (1992) discussed the advantages and drawbacks related to using seasonal flow data to estimate the annual peak flow distribution but did not explicitly focus on flood estimation in sub-yearly periods. Similarly, Kochanek et al (2012) and focused on the upper quantiles of the annual peak flows by fitting data collected in two seasons. Other analogous contributions were provided by Buishand and Demarè (1990), who refer to rainfall depths, and Singh et al (2005).…”

Section: Introductionmentioning

confidence: 99%

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Estimating the flood frequency distribution at seasonal and annual time scales

Baratti

Montanari

Castellarin

et al. 2012

Hydrol. Earth Syst. Sci.

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Abstract.We propose an original approach to infer the flood frequency distribution at seasonal and annual time scale. Our purpose is to estimate the peak flow that is expected for an assigned return period T , independently of the season in which it occurs (i.e. annual flood frequency regime), as well as in different selected sub-yearly periods (i.e. seasonal flood frequency regime). While a huge literature exists on annual flood frequency analysis, few studies have focused on the estimation of seasonal flood frequencies despite the relevance of the issue, for instance when scheduling along the months of the year the construction phases of river engineering works directly interacting with the active river bed, like for instance dams. An approximate method for joint frequency analysis is presented here that guarantees consistency between fitted annual and seasonal distributions, i.e. the annual cumulative distribution is the product of the seasonal cumulative distribution functions, under the assumption of independence among floods in different seasons. In our method the parameters of the seasonal frequency distributions are fitted by maximising an objective function that accounts for the likelihoods of both seasonal and annual peaks. In contrast to previous studies, our procedure is conceived to allow the users to introduce subjective weights to the components of the objective function in order to emphasize the fitting of specific seasons or of the annual peak flow distribution. An application to the time series of the Blue Nile daily flows at the Sudan-Ethiopia border is presented.

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Section: Estimation Of Seasonal and Annual Flood Frequency Distributionssupporting

confidence: 69%

Section: Season Identificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimating the flood frequency distribution at seasonal and annual time scales

Baratti

Montanari

Castellarin

et al. 2012

Hydrol. Earth Syst. Sci.

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“…Laio et al, 2009). Literature shows recent advances on how to combine different theoretical models together to improve the representation of the local flood frequency regime through multimodel approaches when the reproduction provided by a single theoretical model is not satisfactory (Bogdanowicz, 2010;Kochanek et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Regional parent flood frequency distributions in Europe – Part 2: Climate and scale controls

Salinas

Castellarin

Kohnová³

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. This study aims to better understand the effect of catchment scale and climate on the statistical properties of regional flood frequency distributions. A database of Lmoment ratios of annual maximum series (AMS) of peak discharges from Austria, Italy and Slovakia, involving a total of 813 catchments with more than 25 yr of record length is presented, together with mean annual precipitation (MAP) and basin area as catchment descriptors surrogates of climate and scale controls. A purely data-based investigation performed on the database shows that the generalized extreme value (GEV) distribution provides a better representation of the averaged sample L-moment ratios compared to the other distributions considered, for catchments with medium to higher values of MAP independently of catchment area, while the three-parameter lognormal distribution is probably a more appropriate choice for drier (lower MAP) intermediate-sized catchments, which presented higher skewness values. Sample L-moment ratios do not follow systematically any of the theoretical two-parameter distributions. In particular, the averaged values of L-coefficient of skewness (L-Cs) are always larger than Gumbel's fixed L-Cs. The results presented in this paper contribute to the progress in defining a set of "process-driven" pan-European flood frequency distributions and to assess possible effects of environmental change on its properties.

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“…Another cause was also that, however theoretically sound, the GEV working perfectly for large samples often fails in far-from-asymptotic samples which we examine in this study. We scrutinised a number of two-and three-parameter distribution functions in terms of their best fit to hydrological annual and seasonal peak flows in Poland and it turned out that despite the regime of the river, other models were preferred rather than GEV Kochanek et al, 2012). However, the crucial argument after the choice of the parent distribution was the pioneering works of Frances et al (1994) 4.…”

Section: Simulation Resultsmentioning

confidence: 99%

Flood frequency analysis supported by the largest historical flood

Strupczewski

Kochanek

Bogdanowicz

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. The use of non-systematic flood data for statistical purposes depends on the reliability of the assessment of both flood magnitudes and their return period. The earliest known extreme flood year is usually the beginning of the historical record. Even if one properly assesses the magnitudes of historic floods, the problem of their return periods remains unsolved. The matter at hand is that only the largest flood (XM) is known during whole historical period and its occurrence marks the beginning of the historical period and defines its length (L). It is common practice to use the earliest known flood year as the beginning of the record. It means that the L value selected is an empirical estimate of the lower bound on the effective historical length M. The estimation of the return period of XM based on its occurrence (L), i.e.M = L, gives a severe upward bias. The problem arises that to estimate the time period (M) representative of the largest observed flood XM.From the discrete uniform distribution with support 1, 2, . . . , M of the probability of the L position of XM, one getsL = M/2. ThereforeM = 2L has been taken as the return period of XM and as the effective historical record length as well this time. As in the systematic period (N ) all its elements are smaller than XM, one can getM = 2 (L + N ) .The efficiency of using the largest historical flood (XM) for large quantile estimation (i.e. one with return period T = 100 years) has been assessed using the maximum likelihood (ML) method with various length of systematic record (N) and various estimates of the historical period lengthM comparing accuracy with the case when systematic records alone (N ) are used only. The simulation procedure used for the purpose incorporates N systematic record and the largest historic flood (XM i ) in the period M, which appeared in the L i year of the historical period. The simulation results for selected two-parameter distributions, values of their parameters, different N and M values are presented in terms of bias and root mean square error (RMSEs) of the quantile of interest are more widely discussed.

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On seasonal approach to flood frequency modelling. Part II: flood frequency analysis of Polish rivers

Cited by 32 publications

References 17 publications

Estimating the flood frequency distribution at seasonal and annual time scales

Estimating the flood frequency distribution at seasonal and annual time scales

Regional parent flood frequency distributions in Europe – Part 2: Climate and scale controls

Flood frequency analysis supported by the largest historical flood

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