| Construction and application of comprehensive drought index based on kernel entropy component analysis |
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| DOI：10.7606/j.issn.1000-7601.2021.01.20 |
| Key Words: kernel entropy component analysis (KECA) comprehensive drought construction of drought index application Heihe River Basin |
| Author Name | Affiliation | | GUO Shengming | College of Water Resources and Architecture Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China | | SU Xiaoling | College of Water Resources and Architecture Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
Key Laboratory of Arid Area Agricultural Water and Soil Engineering, Ministry of Education, Northwest A&F University, Yangling, Shaanxi 712100 | | WU Haijiang | College of Water Resources and Architecture Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China | | JIANG Tianliang | College of Water Resources and Architecture Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China | | LIANG Zheng | College of Water Resources and Architecture Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China | | FENG Kai | College of Water Resources and Architecture Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China |
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| Abstract: |
| In view of the cavity that the traditional single variable drought indices are difficult to characterize the comprehensive drought situation, and some existed composite drought indices reflect poorly on the nonlinear relationship among multiple variables. We adopted kernel entropy component analysis (KECA) to construct a comprehensive drought index (SMDI) by considering three various single drought indices: the standardized precipitation evaporation index (SPEI) to represent meteorological drought, standardized runoff index (SRI) to characterize hydrological drought, and standardized soil moisture index (SSMI) to show agricultural drought. Taking the upper and middle reaches of Heihe River Basin as an example to analyze the drought spatiotemporal variation and the applicability of SMDI, the M-K trend test, wavelet analysis and typical historical drought events validation were utilized. The results showed that 77.6% of the grids of the study area presented an insignificant worsening trend of drought in the whole year. Drought had a long period of 43 a, a medium period of 15~23 a and a short period of 3~8 a on the watershed scale. In the season of summer and autumn of 1990s as well as in spring and winter since the 21st century, the drought frequency was higher. Moreover, the overall frequency of summer drought was virtually the highest. The typical historical drought events test in the spring 1969, autumn 1997, and winter 2009 also argued that SMDI was superior to the other three univariate drought indices. As such, the KECA-based SMDI was an effective drought monitoring index and had better applicability in the upper and middle Heihe River Basin. |
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