COMPARISON OF ANNUAL MAXIMUM SERIES AND PARTIAL DURATION SERIES METHODS FOR MODELING EXTREME HYDROLOGIC EVENTS .1. AT-SITE MODELING

Two different models for analyzing extreme hydrologic events, based on , respectively, partial duration series (PDS) and annual maximum serie s (AMS), are compared. The PDS model assumes a generalized Pareto dist ribution for modeling threshold exceedances corresponding to a general ized extreme value distribution for annual maxima. The performance of the two models in terms of the uncertainty of the T-year event estimat or is evaluated in the cases of estimation with, respectively, the max imum likelihood (ML) method, the method of moments (MOM), and the meth od of probability weighted moments (PWM). In the case of ML estimation , the PDS model provides the most efficient T-year event estimator. In the cases of MOM and PWM estimation, the PDS model is generally prefe rable for negative shape parameters, whereas the AMS model yields the most efficient estimator for positive shape parameters. A comparison o f the considered methods reveals that in general, one should use the P DS model with MOM estimation for negative shape parameters, the PDS mo del with exponentially distributed exceedances if the shape parameter is close to zero, the AMS model with MOM estimation for moderately pos itive shape parameters, and the PDS model with ML estimation for large positive shape parameters. Since heavy-tailed distributions, correspo nding to negative shape parameters, are far the most common in hydrolo gy, the PDS model generally is to be preferred for at-site quantile es timation.