Regional flood frequency analysis in arid regions: A case study for Australia

Zaman, Mohammad A; Rahman, Ataur; Haddad, Khaled

doi:10.1016/j.jhydrol.2012.08.054

Cited by 96 publications

(69 citation statements)

References 36 publications

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“…Previous studies used both the annual maximum (AM) and peak over threshold (POT) series (commonly known as partial series) to estimate flood frequency in Australia (e.g., [13][14][15]) and elsewhere (e.g., [16][17][18]). The advantage of the AM series is that flood events can be considered independent, flood data can be extracted easily and frequency distributions generally conform to theoretical distributions.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Annual Maximum and Partial Duration Series for Estimating Frequency of Small Magnitude Floods

Karim

Hasan

Marvanek

2017

Water

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Understanding the nature of frequent floods is important for characterising channel morphology, riparian and aquatic habitat, and informing river restoration efforts. This paper presents results from an analysis on frequency estimates of low magnitude floods using the annual maximum and partial series data compared to actual flood series. Five frequency distribution models were fitted to data from 24 gauging stations in the Great Barrier Reef (GBR) lagoon catchments in north-eastern Australia. Based on the goodness of fit test, Generalised Extreme Value, Generalised Pareto and Log Pearson Type 3 models were used to estimate flood frequencies across the study region. Results suggest frequency estimates based on a partial series are better, compared to an annual series, for small to medium floods, while both methods produce similar results for large floods. Although both methods converge at a higher recurrence interval, the convergence recurrence interval varies between catchments. Results also suggest frequency estimates vary slightly between two or more partial series, depending on flood threshold, and the differences are large for the catchments that experience less frequent floods. While a partial series produces better frequency estimates, it can underestimate or overestimate the frequency if the flood threshold differs largely compared to bankfull discharge. These results have significant implications in calculating the dependency of floodplain ecosystems on the frequency of flooding and their subsequent management.

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Section: Introductionmentioning

confidence: 99%

Evaluating Annual Maximum and Partial Duration Series for Estimating Frequency of Small Magnitude Floods

Karim

Hasan

Marvanek

2017

Water

View full text Add to dashboard Cite

show abstract

“…As mentioned above, all the stations have more than 40 years of record length, and 17 stations have more than 50 years of record length. But compared to other international studies on regional frequency analysis (Fowler and Kilsby, 2003;Saf, 2010;Zaman et al, 2012), stations in the Qiantang River Basin distribute slightly dispersedly. Therefore, according to the pedigree matrix, the score of the empirical quality is set to 3.5.…”

Section: Integrated Assessment Of Uncertaintiesmentioning

confidence: 59%

Qualitative and quantitative uncertainties in regional rainfall frequency analysis

Zhu

Gao

et al. 2015

J. Zhejiang Univ. Sci. A

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Uncertainty exists widely in hydrological analysis, and this makes the process of uncertainty assessment very important for making robust decisions. In this study, uncertainty sources in regional rainfall frequency analysis are identified for the first time. The numeral unite spread assessment pedigree (NUSAP) method is introduced and is first employed to quantify qualitative uncertainty in regional rainfall frequency analysis. A pedigree matrix is particularly designed for regional rainfall frequency analysis, by which the qualitative uncertainty can be quantified. Finally, the qualitative and quantitative uncertainties are combined in an uncertainty diagnostic diagram, which makes the uncertainty evaluation results more intuitive. From the integrated diagnostic diagram, it can be determined that the uncertainty caused by the precipitation data is the smallest, and the uncertainty from different grouping methods is the largest. For the downstream sub-region, a generalized extreme value (GEV) distribution is better than a generalized logistic (GLO) distribution; for the south sub-region, a Pearson type III (PE3) distribution is the better choice; and for the north sub-region, GEV is more appropriate.

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“…If A 2 ą A 2 α (the critical value at the significance level α), the hypothesis regarding the distributional form is rejected [31].…”

Section: Probability Modelingmentioning

confidence: 99%

Frequency Analysis of High Flow Extremes in the Yingluoxia Watershed in Northwest China

Wang

Zhao

et al. 2016

Water

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Statistical modeling of hydrological extremes is significant to the construction of hydraulic engineering. This paper, taking the Yingluoxia watershed as the study area, compares the annual maximum (AM) series and the peaks over a threshold (POT) series in order to study the hydrological extremes, examines the stationarity and independence assumptions for the two series, and discusses the estimations and uncertainties of return levels from the two series using the Generalized Extreme Value (GEV) and Generalized Pareto distribution (GPD) models. For comparison, the return levels from all threshold excesses with considering the extremal index are also estimated. For the POT series, the threshold is selected by examining the mean excess plot and the stability of the parameter estimates and by using common-sense. The serial correlation is reduced by filtering out a set of dependent threshold excesses. Results show that both series are approximately stationary and independent. The GEV model fits the AM series well and the GPD model fits the POT series well. The estimated return levels are fairly comparable for the AM series, the POT series, and all threshold excesses with considering the extremal index, with the difference being less than 10% for return periods longer than 10 years. The uncertainties of the estimated return levels are the highest for the AM series, and next for the POT series and then for all threshold excesses series in turn.

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Regional flood frequency analysis in arid regions: A case study for Australia

Cited by 96 publications

References 36 publications

Evaluating Annual Maximum and Partial Duration Series for Estimating Frequency of Small Magnitude Floods

Evaluating Annual Maximum and Partial Duration Series for Estimating Frequency of Small Magnitude Floods

Qualitative and quantitative uncertainties in regional rainfall frequency analysis

Frequency Analysis of High Flow Extremes in the Yingluoxia Watershed in Northwest China

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