In this paper, an analysis of adapted 20 extreme precipitation indices is calculated for a limited mountain area in southern Vietnam. The daily precipitation data from four stations in the period of more than 30 years...In this paper, an analysis of adapted 20 extreme precipitation indices is calculated for a limited mountain area in southern Vietnam. The daily precipitation data from four stations in the period of more than 30 years are selected. The statistical characteristics of maximum, minimum, mean, standard deviation, skewness, and kurtoris for each index are also analysed. A variety of distributions such as Normal, Lognormal, Beta, Gamma, Exponential, Loglogistic, and Johnson is used to find the best fit probability distribution for this area on the basic of the highest score. The scores are estimated based on the ranking of statistical goodness of fit test. The goodness of fit tests is the Anderson-Darling and Shapiro-Wilks tests. The best fit distribution for each index of extreme precipitation at each station is found out. Results revealed that the Johnson distribution is the best fit distribution to the data of very heavy precipitation days greater than 50 mm. Over a limited mountain area, it is difficult to fit a probability distribution to the precipitation fraction due to extremely wet days, number of extremely wet days, and number of extremely wet days when precipitation greater than 99 percentage. The lognormal, Johnson, and Loglogistic distribution are the best choices to fit most of the extreme precipitation indices over this area.展开更多
文摘In this paper, an analysis of adapted 20 extreme precipitation indices is calculated for a limited mountain area in southern Vietnam. The daily precipitation data from four stations in the period of more than 30 years are selected. The statistical characteristics of maximum, minimum, mean, standard deviation, skewness, and kurtoris for each index are also analysed. A variety of distributions such as Normal, Lognormal, Beta, Gamma, Exponential, Loglogistic, and Johnson is used to find the best fit probability distribution for this area on the basic of the highest score. The scores are estimated based on the ranking of statistical goodness of fit test. The goodness of fit tests is the Anderson-Darling and Shapiro-Wilks tests. The best fit distribution for each index of extreme precipitation at each station is found out. Results revealed that the Johnson distribution is the best fit distribution to the data of very heavy precipitation days greater than 50 mm. Over a limited mountain area, it is difficult to fit a probability distribution to the precipitation fraction due to extremely wet days, number of extremely wet days, and number of extremely wet days when precipitation greater than 99 percentage. The lognormal, Johnson, and Loglogistic distribution are the best choices to fit most of the extreme precipitation indices over this area.
