Joint use of L-moment diagram and goodness-of-fit test: a case study of diverse series

Ben‐Zvi, Arie; Azmon, B.

doi:10.1016/s0022-1694(96)03302-1

Cited by 30 publications

(9 citation statements)

References 11 publications

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“…L-moments based regional frequency analysis is practiced all over the world (for example, Guttman et al 1993;Smithers and Schulze 2001;Ben-Zvi and Azmon 1997;Pandey et al 2001;Elamir and Seheult 2001;Jingyi and Hall 2004;Saf 2009;Eslamian and Feizi 2007;Modarres 2007;Norbiato et al 2007;Hussain and Pasha 2009;Castellarin et al 2008;Yang et al 2009) but an important aspect, in the comparison of quality of the quantile estimates obtained at each site from regional approach to that of at-site analysis, is how can we calculate the standard errors of the estimated quantiles at each site of a homogeneous region? In this paper, a relationship provided in Hosking and Wallis (1997) has been explored and standard errors of the estimated flood quantiles at each site of the homogeneous regions have been calculated by extending the results of the simulation experiments related to the accuracy measures of the regional estimates.…”

Section: Introductionmentioning

confidence: 99%

Application of the Regional Flood Frequency Analysis to the Upper and Lower Basins of the Indus River, Pakistan

Hussain

2011

Water Resour Manage

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The paper presents results of an application of the L-moments based regional flood frequency analysis to annual maximum peak (AMP) flows observed at seven stations (Tarbela, Kalabagh, Chashma, Taunsa, Guddu, Sukkur and Kotri) located on the main stream of the Indus River, Pakistan. The results of Run-test and lag-1 correlation coefficient showed that the data series at given sites is random and has no serious serial correlations respectively. Furthermore, the results of Grubbs and Beck test illustrated that there are no irregularities (abrupt variations) except low outlier(s) in the data series at various sites. To avoid their undue influence, these low outliers have been discarded and the sample information has been resummarized using the idea of left censored type A partial probability weighted moments. L-moments based regional heterogeneity measure (H) showed that the region, defined by seven stations, is heterogeneous; therefore, it has been sub-divided into two homogeneous regions (Region 1 and Region 2 consist of four (Tarbela, Kalabagh, Chashma and Taunsa) and three sites (Guddu, Sukkur and Kotri, respectively) using Ward's clustering method based on the site characteristics only. The results of various goodness-of-fit measures (L-moment ratio diagram, average weighted distance and Z DIST measures) showed that Region 1 has four candidates: generalized normal (GNO), generalized logistic (GLO), generalized extreme-value (GEV) and Pearson type III (PE3), while Region 2 has only one candidate; GLO, as regional distribution. Based on the results of different accuracy measures (regional average absolute relative bias, relative bias and relative root mean square error) of the estimated regional growth curves and quantiles, obtained from simulation experiments, PE3 is the robust distribution for Region 1, while for Region 2, GLO distribution can be used for the estimation of flood quantiles. Moreover, the results of the simulations study have been extended to obtain standard errors of the estimated quantiles at each site of the sub-divided homogeneous regions.

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Section: Introductionmentioning

confidence: 99%

Application of the Regional Flood Frequency Analysis to the Upper and Lower Basins of the Indus River, Pakistan

Hussain

2011

Water Resour Manage

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“…The k-s test and AD tests perform better than the Chi-Squared [21], with the AD deemed as more powerful as it places more emphasis on tail end of the distribution [22]. The critical values for the k-s and AD tests change based on the theoretical probability distribution considered and number of parameters being estimated, with various works [23][24][25][26] published on this matter.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Linear Moments and Uncertainty Analysis to Extreme Rainfall Events in Sabah

2017

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Abstract. Linear moments (LM) has been applied in extreme rainfall study for several countries, including China, United States of America, and Peninsular Malaysia. In this study, the LM procedures were applied to extreme rainfall data corresponding to locations provided in Malaysia Urban Stromwater Manual (MSMA) to derive new design rainfalls. Different record lengths were considered to assess the changes in design rainfall, and Monte Carlo simulations were carried out to compute confidence interval of the derived design rainfalls. Based on the Goodnessof-Fit (GoF) test results, the Generalized Extreme Value (GEV) probability distribution was chosen to derive the design rainfalls. The updated design rainfalls at all four locations showed significant reduction at design rainfalls of 50-year ARI and above. The difference of the design rainfalls from shorter record lengths with respect to the full record length and the confidence intervals do not necessarily reduce with a longer record. In hypothetical cases where 100-yr ARI rainfall was added, the increase in design rainfalls did not exceed the upper bound of the confidence intervals. The derived confidence intervals hence allow for better risk assessment, and should be considered in the design of critical structures, i.e. dams.

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“…Although the 1% flood values were not given for each site by Shentsis et al (1997), maximum observed flows for most of these sites are presented by Ben Zvi & Azmon (1997), and values for Region I are plotted on Fig. 3(a).…”

Section: Regional Distribution Of Maximum Instantaneous Flowsmentioning

confidence: 99%

Preliminary flood frequency estimates for Lebanon

Sene

Houghton-Carr

Hachache

2001

Hydrological Sciences Journal

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This paper describes a first attempt at developing a regional flood estimation methodology for Lebanon. The analyses are based on instantaneous flood peak data for the whole country, and cover the period from the start of observations in the 1930s to the start of the civil war in the mid-1970s. Three main flood-generating zones are identified, and regional flood growth curves are derived for each zone using the Generalized Extreme Value distribution fitted by probability-weighted moments.Typical parameter values are presented, together with regression coefficients for estimating the mean annual flood. Based on this work, several recommendations are made on the future data collection and analysis requirements to develop a national flood estimation methodology for Lebanon.

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Joint use of L-moment diagram and goodness-of-fit test: a case study of diverse series

Cited by 30 publications

References 11 publications

Application of the Regional Flood Frequency Analysis to the Upper and Lower Basins of the Indus River, Pakistan

Application of the Regional Flood Frequency Analysis to the Upper and Lower Basins of the Indus River, Pakistan

Application of Linear Moments and Uncertainty Analysis to Extreme Rainfall Events in Sabah

Preliminary flood frequency estimates for Lebanon

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