000			a
999			_c19575 _d19575
003			OSt
005			20230628163406.0
008			230628b xxu||||| |||| 00| 0 eng d
040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_921283 _aVivekananand, N.
245			_a COMPARISON OF EXTREME RAINFALL ESTIMATES USING L-MOMENTS OF SIX PROBABILITY DISTRIBUTIONS
250			_aVol,41(2), Apr
260			_aRoorkee _bIndian Water Resources Society _c2021
300			_a35-40p
520			_aEstimation of rainfall for a given return period is utmost importance for planning, design and management of hydraulic structures. This can be achieved through Extreme Value Analysis (EVA) by fitting probability distributions (PDs) to the series of annual 1-day maximum rainfall data. In this paper, a study on comparison of extreme rainfall estimates using L-Moments (LMO) of six PDs such as Exponential, Extreme Value Type-1, Extreme Value Type-2, Generalized Extreme Value (GEV), Generalized Pareto and Log-Normal for Afzalpur and Kalaburagi sites is carried out. The adequacy of fitting six PDs adopted in EVA of rainfall is quantitatively assessed by applying the Goodness-of-Fit (GoF) (viz., Chi-square and Kolmogorov-Smirnov) and diagnostic (viz., D-index) tests, and qualitatively assessed by using the probability plots of the estimated rainfall. The EVA results of rainfall indicate the GEV (using LMO) is better suited amongst six PDs adopted for estimation of rainfall at Afzalpur and Kalaburagi sites
650		0	_94621 _aCivil Engineering
773	0		_x0970-6984 _tJournal of indian water resource society _dRoorkee Indian Institute of Technology Roorkee
856			_uhttps://iwrs.org.in/journal/apr2021/6apr.pdf _yClick here
942			_2ddc _cAR