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Accuracy of parameter estimation methods to be used in extreme value analyses for censored annual maximum samples is investigated using a Monte-Carlo simulation technique. The methods are maximum likelihood method (MLM), least square method (LSM) and partial probability weighted moment (PPWM) method, and probability distributions are Gumbel, shape parameter-fixed GEV and Weibull distributions. MLM yields more efficient estimates of quantiles than PPWM method and LSM even for censored samples. MLM-, LSM- and PPWM-based models are applied to extreme value analyses to several types of censored in-situ annual maximum samples. One finding is that inclusion of historical information in MLM- and PPWM-based models produces more efficient estimates of quantiles.

INTERCOMPARISON OF EXTREME VALUE ANALYSES FOR CENSORED ANNUAL MAXIMUM SAMPLE