Identification of the underlying distribution form of precipitation by using regional data

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Abstract
A method of identifying the underlying distribution form for precipitation is proposed in this paper. This method is different from the classical hypothesis‐testing method and is based upon using regional data. Two fundamental assumptions are made: (1) the distribution forms of rainfall at all stations in a studied area are the same, and the thirdLmoment ratios, τ3, at all stations are also the same; and (2) the unknown underlying distribution form is one among five commonly used distributions: i.e., generalized extreme value (GEV), gamma (GAM), lognormal (LON), generalized Pareto (PAR), and generalized logistic distribution (LGI). Using the proposed method, one can not only choose a distribution form for the given data, but also know the probability that the identification is correct. For a parameter within the range commonly occurring in practice, this probability is reasonably high. Therefore the proposed method would be valuable and informative.