L-moment and composite model approaches for regional flood frequency analysis. (2015)

• Record Type: Journal Article
• Authors: Yarrakula, Kiran; Samanta, Biswajit; Deb, Debasis
• Is Part Of: International journal of hydrology science and technology. Volume 5:Number 2(2015)
• Page Start: 95
• Page End: 118
• Publication Date: 2015
• Subjects: best fit contribution -- frequency analysis -- artificial neural networks -- ANNs -- Z-statistic -- homogeneity -- L-moment -- composite modelling -- regional floods -- flood frequency -- flooding -- hydraulic structures -- structural design -- India; Hydrology -- Periodicals; Water resources development -- Periodicals; Hydrology; 553.705
• Languages: English
• ISSNs: 2042-7808

Abstract

In the design of hydraulic structures such as dams, culverts and urban drainage systems, flood frequency analysis plays a significant role. In this study, regional flood frequency analysis based on L-moment and neural network approach based on composite model has been carried out for the Subernarekha River, India. To identify the homogeneous regions, heterogeneous test and screening of the data with discordance measure have been performed. For calculating heterogeneity, 500 simulations are conducted using four parameter Kappa distribution. PE-III distribution is identified as best distribution for the study area based on L-moment ratio diagram and |Zdist|-statistic. Error statistics of regional quantile estimates for different distributions and composite model have been performed. The R² values of composite model for the quantile range below 0.99 and above 0.99 are 0.995 and 0.993 respectively. The growth factors for composite model and PEIII for the 50 years return period are 2.10 and 2.3 respectively.