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Intercomparison of Rainfall Estimates of EV1 Distribution for Estimation of Peak Flood Discharge for Ungauged Catchments

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  • N. Vivekanandan

Abstract

Estimation of Peak Flood Discharge (PFD) for a return period is one of the important parameters for planning, design and management of hydraulic structures such as dams, bridges, barrages and storm water drainage systems. For ungauged catchments, rainfall depth becomes an important input for estimation of PFD. The rainfall depth can be determined through Extreme Value Analysis (EVA), which involves fitting of probability distribution to the series of Annual 1-day Maximum Rainfall (AMR) data. In this paper, the AMR series derived from the daily rainfall data observed at Dehra site is used for EVA adopting Extreme Value Type-1 (EV1) distribution. Standard parameter estimation methods such as method of moments, method of least squares, maximum likelihood method, principle of maximum entropy, Probability Weighted Moments (PWM) and L-moments are applied for determination of parameters of the EV1 distribution. The adequacy of fitting of EV1 distribution adopted in EVA is evaluated by Goodness-of-Fit tests viz., Anderson-Darling and Kolmogorov-Smirnov (KS) and diagnostic tests viz., root mean squared error and mean absolute error. The KS and diagnostic tests results indicated that the PWM is better-suited method for determination of parameters of EV1 distribution, which is adopted for EVA of rainfall. The 1-hour distributed rainfall computed from the estimated extreme rainfall adopting EV1 (using PWM) distribution is used to estimate the PFD by rational formula. The estimated PFD for river Nakehr and its tributaries could be used for design of hydraulic structures.

Suggested Citation

  • N. Vivekanandan, 2018. "Intercomparison of Rainfall Estimates of EV1 Distribution for Estimation of Peak Flood Discharge for Ungauged Catchments," Int J Sci Res Civil Engg, International Journal of Scientific Research in Civil Engineering, vol. 2(4), pages 28-40, August.
    • Handle: RePEc:jcq:ijsrce:v2:y2018:i4:id:119
    DOI: 10.32628/IJSRCE18241
    Note: Article URL: https://ijsrce.com/home/article/view/IJSRCE18241
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