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Global Scholars Journal of Earth Science and Astronomy Vol.1 (1), pp. 1-9 December, 2013
©2013 Global Scholars Journals.

 

Full Length Research Paper

Assessing the adequacy of parameter estimation method of Gumbel distribution for modelling annual 1-day maximum rainfall

N. Vivekanandan

Central Water and Power Research Station, Pune 411024, India.

E-mail: anandaan@rediffmail.com.

Accepted 12 December 2013

 

 

 

   
   
   
   
   
   
   
   
   
   
  Abstract  
 

Estimation of design flood for a desired return period is of utmost importance for planning, design and management of hydraulic structures at the project site. This can be achieved by fitting of probability distribution to the recorded Annual 1-day Maximum Rainfall (AMR) data. This paper illustrates the use of Gumbel distribution for modelling AMR recorded at Fatehabad, Hansi, Hissar and Tohana rain-gauge stations. Parameter estimation methods such as method of moments, maximum likelihood method, Method of Least Squares (MLS), Mixed moments (MIX), order statistics approach, principle of maximum entropy and probability weighted moments are used for determination of distributional parameters. Kolmogorov-Smirnov (KS) test is used for checking the adequacy of fitting Gumbel distribution to the recorded data. Model Performance Indicators (MPIs) such as coefficient of determination and root mean square error are used for the selection of a suitable method for modelling AMR. The MPIs results show that the MLS is better suited for modelling AMR for Fatehabad, Hissar and Tohana, and MIX for Hansi; though KS test supports the use of all seven methods for determination of parameters of Gumbel for the stations under study.

Keywords: Gumbel Distribution, Kolmogorov-Smirnov Test, Method of Least Squares, Rainfall Analysis.

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