COMPARISON OF EXTREME RAINFALL ESTIMATES USING L-MOMENTS OF SIX PROBABILITY DISTRIBUTIONS
Publication details: Roorkee Indian Water Resources Society 2021Edition: Vol,41(2), AprDescription: 35-40pSubject(s): Online resources: In: Journal of indian water resource societySummary: Estimation 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| Item type | Current library | Status | Barcode | |
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School of Engineering & Technology (PG) Archieval Section | Not for loan | 2023-0947 |
Estimation 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
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