Low - FLOW FREQUENCY ANALYSiS USING PROBABILITY - PLOT CORRELATION COEFFICIENTS

Although a vast amount of literature exists on the selection of an appropriate probubility distribution for annual maximum fluodflows, few studies huve examined which probability distributions ure most suitable to fit to sequences of annual minimum streamflow!;. Probabilily plots have been u!;ed widely in hydrology as a gruphicul uid to assess the goodnes!; of fu of ultemative distributions. Recently, probubility-plot correlution-cl!efficient (PPCC) te!;ts were introduced to test the normul, two-parameter lognonnul und Gumbel hypotheses. Those procedures are extended here to include both regional und ut-site tests for lhe two-parumeter Weibull und lognonnal distributionul hypotheses. In theory, PPCC-hypothe!;is te!;ts cun only be developed for two-parameter distributions that exhibil a fixed shape. Nevertheless, the PPCC is a useful goodness-of-fit statistic for comparing three-parameter distributions. The PPCC derived from fitting the twoand thrce-pararneter lognonnal, twoand three-purarneter Weibull, and log-Pearson type III distributions to sequences of annual minimum seven-day low flows at 23 sit~s in Massachusetts are compared. How the PPCC can be used to discriminate among both competing distributional hypotheses for the distributions of fixed !;hape and competing pur-dmeter-estimation pn)Cedurcs for the distributions with vuriable shape is described. An upproximate regional PPCC test is developed und used to show that there is almost no evidence to contradict the hypothesis that unnual minimum seven-day low flows in Massachusetts are two-parameter lognonnul.