2009
DOI: 10.1002/met.139
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Regional daily maximum rainfall estimation for Cekerek Watershed by L‐moments

Abstract: ABSTRACT:The estimation of maximum daily rainfall (PDmax) is usually required for the estimation of design flood (the maximum flood that any hydraulic structure can safely pass). However, PDmax estimation is usually required for watersheds where rainfall data are either not available or only available in short periods from various sites and so are unsuitable for maximum daily rainfall estimation. In this study, the regional PDmax of the Cekerek watershed in Turkey is estimated using the method of l-moments usi… Show more

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Cited by 28 publications
(16 citation statements)
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“…The L-moments method had been employed for parameter estimation of the stationary GEV models in this study since it is less affected from data variability and outliers, and relatively unbiased for small samples (Borijeni and Sulaiman 2009). Details of the L-moments method can be found in Yurekli et al (2009).…”
Section: Stationary and Non-stationary Generalized Extreme Value Distmentioning
confidence: 99%
“…The L-moments method had been employed for parameter estimation of the stationary GEV models in this study since it is less affected from data variability and outliers, and relatively unbiased for small samples (Borijeni and Sulaiman 2009). Details of the L-moments method can be found in Yurekli et al (2009).…”
Section: Stationary and Non-stationary Generalized Extreme Value Distmentioning
confidence: 99%
“…Casas et al (2007) used 145 pluviometric stations for regional estimation of extreme rainfall in Catalonia using L-moments. More recently, Yurekli et al (2009) found GEV and LN3 distributions as the regional distribution functions for the maximum daily rainfall of Cekerec watershed, Turkey, through the L-moment approach.…”
Section: Introductionmentioning
confidence: 99%
“…22 in the original paper), the best distributions were correctly selected as shown in Table 4 of the original paper. Not depicting the L-moment ratio diagram for the Generalized Pareto Distribution does not make any problem for the best fitted distribution selection procedure as similarly done in many recent studies (Yurekli et al 2009;Modarres 2010;Modarres and Sarhadi 2010;Nasri and Moradi 2011;Eslamian et al 2012). The discussers changed the homogeneous regions and reclustered the region and finally selected the best distribution based on new clusters, which obviously may result in different findings.…”
Section: Introductionmentioning
confidence: 88%