FITTING OF THE GEV, GLO AND GPA DISTRIBUTIONS WITH TRIMMED L MOMENTS (1, 1) IN 21 ANNUAL FLOOD RECORDS OF THE HYDROLOGICAL REGION No. 10 (SINALOA), MEXICO

Abstract

The hydrological dimensioning and security of all water use or control works depend on the flood design. The reliable estimation of those hydrologic magnitudes is related to the availability of the most accurate possible maximum annual discharge data and their representation, in a probability distribution function (PDF). The method of L moments, which are linear combinations of the order statistics, is one of the most accurate fitting procedures that allow to estimate the parameters of an PDF. Robust versions have been proposed for L moments, since they give no weight to the extreme values of the sample; such is the case of the trimmed L moments (1,1), which do not take into account the lowest nor the highest data. This study presents both fitting methods for the PDFs general extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA), which are probability models with worldwide acceptance in the frequency analysis of hydrological extreme data. Using the standard error of fit (SEF) the contrast was performed for the application of the mentioned PDFs, to 21 records of annual floods available in the Hydrological Region No. 10 (Sinaloa, Mexico). The results indicated that the PDFs led to the lowest SEFs in three, seven, and eleven of the records processed. The method of adjustment by trimmed L moments (1,1) achieved a lower SEF in ten of the records processe. Therefore, its systematic use is recommended in the frequency analyses of extreme hydrological data.