Meteorological to Agricultural Drought Propagation Time Analysis and Driving Factors Recognition Considering Time-Variant Characteristics

Chengguo Wu, Yin Xu, Juliang Jin, Yuliang Zhou (), Boyu Nie, Rui Li, Yi Cui, Fei Tong and Libing Zhang
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Chengguo Wu: Hefei University of Technology
Yin Xu: Hefei University of Technology
Juliang Jin: Hefei University of Technology
Yuliang Zhou: Hefei University of Technology
Boyu Nie: Hefei University of Technology
Rui Li: Hefei University of Technology
Yi Cui: Hefei University of Technology
Fei Tong: Hefei University of Technology
Libing Zhang: Hefei University of Technology

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 3, No 10, 1010 pages

Abstract: Abstract Drought propagation analysis is of great significance to develop reliable drought-resistant schemes. In this study, based on the construction of time-variant meteorological and agricultural drought indicators SPIt and SSMIt through Generalized Additive Models for Location, Scale and Shape (GAMLSS) method, the static and dynamic drought propagation time were defined and determined by Five-element Subtraction Set Pair Potential (FSSPP) and Copula function methods. Then, the driving factors resulted in meteorological to agricultural drought propagation were recognized through Pearson Correlation Coefficient (PCC) indicator. And finally, the application results of the proposed approach in Anhui province, China indicated that, (1) the static propagation time of meteorological to agricultural drought process varied within 1 to 4 months, and differed slightly in different seasons. And drought propagation time in spring and summer was noticeably longer than that of autumn and winter. (2) the dynamic drought propagation time presented decreasing trend in winter, spring and summer but displayed slight increasing trend in autumn in Anhui province. On the whole, the research findings are beneficial for theoretical and practical research of drought propagation system.

Keywords: Drought propagation; Time-variant drought indicator; GAMLSS; FSSPP; Copulas function; Anhui province (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11269-023-03705-8

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