LOW FLOW FREQUENCY ANALYSIS BY L-MOMENTS METHOD (CASE STUDY: IRANIAN CENTRAL PLATEAU RIVER BASIN)

Abstract

Knowledge about low flow statistics is essential for effective water resource planning and management in ungauged orpoorly gauged catchment areas, especially in arid and semi-arid regions such as Iran. We employed a data set of 20 riverflow time-series from the Iranian Central Plateau River Basin, Iran to evaluate the low-flow series using several frequencyanalysis methods and compared the result of these methods in their ability to set low flows for the conservation ofinstream water uses. Theoretical frequency distributions including the log-normal, three-parameter lognormal, Gumbel,Pearson type III, and log Pearson type III were applied with the low-flow series. Goodness-of-fit tests including Lmomentand conventional moment methods for the observed data were applied to identify the best distributions. For eachdistribution, the calculated values of the residual sum of squares (RSS) was applied to compare between the conventionalmoment and L-moment methods, and the best method was selected to determine the most appropriate probabilitydistribution. The lowest RSS values were used to select the best distribution for each station. Then, T-year low-flow serieswas estimated using the best probability distribution. Our results suggested that, for annual low flows, based on thecomputed RSS, Pearson type III, log Pearson type III, Gumbel distributions, and L-moment method were suitablydistinguished for 85%, 10%, and 5% of the stations, respectively. Finally, Compared to the conventional moment method,L-moments method was found to be more adequate to identify low-flow series probability distributions in the IranianCentral Plateau River Basin, while Pearson type III was found to be the best probability distribution for modelingminimum flow series in the study area.