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Rescaled Statistics and Wavelet Analysis on Agricultural Drought Disaster Periodic Fluctuations in China from 1950 to 2016

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  • Qian Wang

    (Department of Ecology, School of Life Sciences, Nanjing University, Nanjing 210093, China)

  • Yangyang Liu

    (Department of Ecology, School of Life Sciences, Nanjing University, Nanjing 210093, China)

  • Linjing Tong

    (Department of Ecology, School of Life Sciences, Nanjing University, Nanjing 210093, China)

  • Weihong Zhou

    (Department of Ecology, School of Life Sciences, Nanjing University, Nanjing 210093, China)

  • Xiaoyu Li

    (Department of Ecology, School of Life Sciences, Nanjing University, Nanjing 210093, China)

  • Jianlong Li

    (Department of Ecology, School of Life Sciences, Nanjing University, Nanjing 210093, China)

Abstract

An agricultural drought disaster was analyzed with the new insight of rescaled statistics (R/S) and wavelet analysis in this study. The results showed that: (1) the Hurst index of the agricultural disaster area, the inundated area of agricultural drought disaster, and the grain loss was 0.821, 0.874, and 0.953, respectively, indicating that the process of the agricultural drought disaster had stronger positive continuity during the study period; (2) based on the Morlet analysis of the agricultural disaster area, the inundated area of the agricultural drought disaster, and the grain loss of China from 1950 to 2016, the time series of the agricultural drought had multiple time scale features with the periodic variation on a large scale containing the periodic variation on a small scale; and (3) in the last 67 years, the strong wavelet energy spectrum of the agricultural disaster area, the inundated area of the agricultural drought disaster, and the grain loss was at the time scale of ≈22–32 years, ≈24–32 years, and ≈25–32 years, respectively. In addition, the first major period in the agricultural drought disaster area, the inundated area of agricultural drought disaster, and the grain loss had average periods of approximately 16 years, 16 years, and 18 years, respectively.

Suggested Citation

  • Qian Wang & Yangyang Liu & Linjing Tong & Weihong Zhou & Xiaoyu Li & Jianlong Li, 2018. "Rescaled Statistics and Wavelet Analysis on Agricultural Drought Disaster Periodic Fluctuations in China from 1950 to 2016," Sustainability, MDPI, vol. 10(9), pages 1-12, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3257-:d:169335
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    1. Peng Shi & Miao Wu & Simin Qu & Peng Jiang & Xueyuan Qiao & Xi Chen & Mi Zhou & Zhicai Zhang, 2015. "Spatial Distribution and Temporal Trends in Precipitation Concentration Indices for the Southwest China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(11), pages 3941-3955, September.
    2. Sánchez Granero, M.A. & Trinidad Segovia, J.E. & García Pérez, J., 2008. "Some comments on Hurst exponent and the long memory processes on capital markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5543-5551.
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    Cited by:

    1. Ayhan Orhan & Dervis Kirikkaleli & Fatih Ayhan, 2019. "Analysis of Wavelet Coherence: Service Sector Index and Economic Growth in an Emerging Market," Sustainability, MDPI, vol. 11(23), pages 1-12, November.
    2. Ming Li & Fuqiang Cao & Guiwen Wang & Xurong Chai & Lianzhi Zhang, 2020. "Evolutional Characteristics of Regional Meteorological Drought and Their Linkages with Southern Oscillation Index across the Loess Plateau of China during 1962–2017," Sustainability, MDPI, vol. 12(18), pages 1-18, September.

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