Water Resources Management 8:183-201, 1994. 183 © 1994 KluwerAcademic Publishers. Printed in the Netherlands. Frequency Analysis of Upper Cauvery Flood Data by L-Moments A. RAMACHANDRA RAO and KHALED H. HAMED School of Civil Engineering, Purdue University, WestLafayette, IN 47907, U.S.A. (Received: 12 November 1993) Abstract. The objectives of the present study are to investigate the hydrological homogeneity of Upper Cauvery annual maximum flow data and to select a suitable distribution for the frequency analysis. The L-moments method is used in this analysis. The Upper Cauvery river basin is shown to be hydrologically heterogeneous. The 3 parameter log normal and the generalized extreme value distributions are recommended for the frequency analysisof data in this region. Key words: hydrological homogeneity, flood data, L-moments methods 1. Introduction The concept of probability weighted moments (PWM) was introduced by Green- wood et aI. (1979). Since then it has received considerable attention from Landwehr et al. (1979a, b), Hosking et al. (1985), Hosking (1986), Hosking and Wallis (1987) and others. PWM estimates are robust in the presence of outliers. Parameter esti- mates from small samples computed by using the PWM method are sometimes more accurate than even the maximum likelihood (ML) estimates. The PWM method is less complicated than the ML method. With some distributions, such as the symmetrical Lambda and Weibull distributions, explicit expressions for the parameters are obtained by the PWM method, which cannot be done with either the ML or the method of moments (MOM). Hosking (1986, 1990) has defined the L-moments which are analogous to the conventional moments and are estimated by linear combinations of order statistics. They can also be expressed by linear combinations of PWM. Thus, procedure~ based on PWM and L-moments are equivalent. However, L-moments are more convenient because they are directly interpretable as measures of the scale and of the shape of probability distributions. Hosking (1990) has used L-moment ratio diagrams to identify underlying parent distributions and L-moment ratios for testing hypotheses about forms of probability distributions. Hosking and Wallis (1991) extended the use of L-moments and developed statistics that can be used in regional frequency analysis to measure discordancy, regional homogeneity and goodness-of-fit. The objective of the present work is to analyze the annual maximum flow data from the Cauvery River basin in south India by using the L-moment method. Both regional and at-site parameter and quantile estimates are used and the differences