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01-Applied Mathematics & Information Sciences
An International Journal
               
 
 
 
 
 
 
 
 
 
 
 
 
 

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Volumes > Volume 14 > No. 2

 
   

Probabilistic Flood Height Estimation of the Limpopo River at the Beitbridge using r-Largest Order Statistics

PP: 191-204
doi:10.18576/amis/140203
Author(s)
Robert Kajambeu, Caston Sigauke, Alphonce Bere, Delson Chikobvu, Daniel Maposa, Murendeni Maurel Nemukula,
Abstract
The paper presents modelling of uncertainty in extreme return levels of the flood heights of the Limpopo river at the Beitbridge in which the delta and profile likelihood approaches are used in the estimation of the confidence intervals. The modelling approach discussed in this study is a hybrid modelling framework blending a variety of statistical models, techniques and approaches. Monthly flood height data for the years 1992 to 2014 are used. The method is based on a joint generalised extreme value distribution of the r-largest order statistics. The method is more efficient in its use of data than the traditional single maximum observation per block. Estimation of parameters is done using the maximum likelihood method. Using the r-largest order statistics approach, the paper shows that the flood height data can suitably be modelled by the Gumbel class distribution. The 100-year return level is estimated to be 4.981 metres with a confidence interval estimate of (4.886,5.083) using the profile likelihood method. This study is important as it enables accurate estimation of return levels and periods of extreme flood heights. Such analysis helps in risk mitigation, for example, the design of bridges by civil engineers.

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