The development of a novel nonstationary meteorological and hydrological drought index using the climatic and anthropogenic indices as covariates

Hydrometeorological variables such as precipitation and runoff are not necessarily stationary under change environment due to anthropogenic influences and climate change. Therefore, the assumption of stationary of standardized drought indices cannot necessarily be applied in the future. The novelty of this study is to develop a nonstationary multivariate standardized drought index, entitled the Nonstationary Meteorological and Hydrological Drought Index (NMHDI), as an improvement of the Meteorological and Hydrological Drought Index (MHDI). The method used consisted of three parts: (1) simulation of the nonstationary marginal distribution of precipitation data using climatic indices as covariates; (2) the nonstationary probability model fitted to runoff data using the climatic and anthropogenic indices as covariates and; (3) using the time-varying copula model to describe the temporal dependence structure of precipitation and runoff, following which the NMHDI was calculated. The performances of the NMHDI and MHDI was compared at the Huaxian station in Weihe River Basin, western China for the period 1961-2010 to illustrate the capabilities of the NMHDI. Moreover, bivariate frequency analysis was conducted using the two indices. The results indicated that the nonstationary model showed better performance in reproducing the variations in precipitation and runoff data and their dependence structure over time as compared with stationary one. The NMHDI identified more frequent extreme droughts. The improved performance of the NMHDI was attributed to its ability to respond to the continuously changing environment. In addition, the MHDI and NMHDI estimated significantly different recurrence periods. The proposed NMHDI provides a novel approach to comprehensive drought monitoring, and can provide valuable information for drought management policymaking under a changing environment. (c) 2021 Elsevier B.V. All rights reserved.