The risks assessment via a regional approach using multivariate regional frequency clustering method

Abstract

Conventional univariate drought frequency analysis should be replaced by the multivariate framework due to the correlated characteristics, such as duration, peak intensity, and severity. Compared to the bivariate case, trivariate analysis would be more considerable. Furthermore, the absence of historical records has a great impact on the reliability of statistical estimates. Multivariate regional frequency analysis approach would be a better choice for providing reliable information for risks assessment and management purpose. Standardized precipitation evapotranspiration index was used in this study to define and detect drought because of the global warming effect. A method based on the cubic spline interpolation was applied to derive drought samples. Applying the multivariate discordancy and homogeneity test, the Pearl River basin was divided into five homogeneous subregions. Regional distributions including marginal distribution and copula function were chosen based on the goodness-of-fit test. Finally, return periods were computed from a regional perspective to assess the different drought risks. The results indicate that high drought risks might exist in the Pearl River basin and the spatial distinction must be taken seriously. Due to the contradiction of water supply and requirement among different districts or provinces, policies needed to be made seriously and urgently to solve the unbalance between water resource and socioeconomic development.