Evaluation of HHT approach for estimating agricultural drought trend and frequency based on modified soil water deficit index (MSWDI)

Abstract

Accurate estimation of the agricultural drought trend and frequency is important to water resources planning and management. In this study, an effective analysis tool, the Hilbert–Huang Transform (HHT) method, was introduced to estimate the agricultural drought trend and frequency based on modified soil water deficit index (MSWDI). The results indicate that (1) based on HHT multiscale decomposition, the MSWDI of four stations has two intra-annual fluctuations, three intra-decadal fluctuations with periodicities between 1 and 6 years, and two inter-decadal fluctuations; (2) the main periodicities obtained from wavelet analysis can also be detected by HHT analysis. Furthermore, the HHT analysis decomposed more time scale patterns than wavelets; (3) the residue of HHT showed a decreasing trend during the 1960s–1980s but an increasing one since the 1980s for the drought index MSWDI series at most of the stations in the Songnen Plain (SNP). It is consistent with the result of Mann–Kendall and Spearman’s Rho; (4) the drought temporal distribution analysis showed that the relative high drought probability was identified during the initial stage of crop growth. It can be concluded that the HHT analysis is an effective approach to examine multiple time scales of frequencies and trend of agricultural drought from its multiscale decomposition and time–frequency characterization, which can not only be applied for other time series but also have the functions combining the wavelet analysis and non-parameter trend tests. The results of this study could also help and be used to improve the drought prediction and expand the application of HHT method in climatology.