Log-Pearson type 3 distribution and its application in flood frequency analysis. II: Parameter estimation methods

A number of parameter estimation methods for the log-Pearson type 3 distribution have been explored in the hydrologic literature, including the method of moments (MOM) in both log space and real space, maximum likelihood estimators (MLEs), and the method of mixed moments (MXM). Several studies have compared MLE and MXM estimators to a so-called Bulletin 17B MOM estimator, but only marginal gains in accuracy are reported and the conclusions are often conflicting. This paper resolves these discrepancies. The observed performance of MLEs can depend critically on the convergence criteria and parameter constraints. Reasonable constraints on parameters can also improve the performance of log space MOM estimators. The method of mixed moments does very well in comparison to MOM and MLE in the absence of regional information. However, a Monte Carlo analysis demonstrates that log space MOM estimators with regional skew information as recommended by Bulletin 17B are likely to be more attractive, and the more precise the regional skewness information the more precise are these flood quantile estimators. MLEs employing regional skew information are also investigated.