Temporal analysis and the joint probability distribution of rainfall indexes in the Taihu Lake Basin, China

Abstract

Taking the Taihu Lake Basin as an example, in this study, the characteristics of the rainfall factors in the study area were analyzed using daily rainfall data from 1955 to 2019. Three factors, i.e., the contribution rate of the rainfall in the flood season, the rainfall frequency, and the maximum daily rainfall, were selected to determine the optimal probability distribution function for each single factor. Furthermore, the root mean square error goodness-of-fit test was used to determine the optimal copula function for the three-dimensional joint probability distribution characteristics of the rainfall factors. The research results show that the three-dimensional copula joint probability method contains much more information than the results of the single variable probability calculation. The copula function can be used to analyze the multi-dimensional joint distribution of rainfall factors, which can fill the gap in research on multiple rainfall factors.