IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i9p3257-d169335.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/9/3257/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/9/3257/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zheng, Jing & Zhang, Guijun & Tong, Changqing, 2016. "Estimating the self-similar exponent of broad-sense self-similar processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 654-659.
    2. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Papers 2105.09140, arXiv.org, revised Sep 2021.
    3. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    4. Liu, Jian & Cheng, Cheng & Yang, Xianglin & Yan, Lizhao & Lai, Yongzeng, 2019. "Analysis of the efficiency of Hong Kong REITs market based on Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    5. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
    6. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    7. 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.
    8. Trinidad Segovia, J.E. & Fernández-Martínez, M. & Sánchez-Granero, M.A., 2012. "A note on geometric method-based procedures to calculate the Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2209-2214.
    9. V Dimitrova & M Fernández-Martínez & M A Sánchez-Granero & J E Trinidad Segovia, 2019. "Some comments on Bitcoin market (in)efficiency," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-14, July.
    10. Panagiotis Delis & Stavros Degiannakis & Konstantinos Giannopoulos, 2023. "What Should be Taken into Consideration when Forecasting Oil Implied Volatility Index?," The Energy Journal, , vol. 44(5), pages 231-250, September.
    11. Doucoure, Boubacar & Agbossou, Kodjo & Cardenas, Alben, 2016. "Time series prediction using artificial wavelet neural network and multi-resolution analysis: Application to wind speed data," Renewable Energy, Elsevier, vol. 92(C), pages 202-211.
    12. Li, Sijia & Wang, Jinman & Zhang, Min & Tang, Qian, 2021. "Characterizing and attributing the vegetation coverage changes in North Shanxi coal base of China from 1987 to 2020," Resources Policy, Elsevier, vol. 74(C).
    13. Paweł Prokop & Adam Walanus, 2017. "Impact of the Darjeeling–Bhutan Himalayan front on rainfall hazard pattern," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(1), pages 387-404, October.
    14. Venelina Nikolova & Juan E. Trinidad Segovia & Manuel Fernández-Martínez & Miguel Angel Sánchez-Granero, 2020. "A Novel Methodology to Calculate the Probability of Volatility Clusters in Financial Series: An Application to Cryptocurrency Markets," Mathematics, MDPI, vol. 8(8), pages 1-15, July.
    15. M. Fern'andez-Mart'inez & M. A S'anchez-Granero & Mar'ia Jos'e Mu~noz Torrecillas & Bill McKelvey, 2016. "A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks," Papers 1601.04188, arXiv.org.
    16. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    17. Zhou, Weijie & Dang, Yaoguo & Gu, Rongbao, 2013. "Efficiency and multifractality analysis of CSI 300 based on multifractal detrending moving average algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1429-1438.
    18. Benjamin Rainer Auer, 2018. "Are standard asset pricing factors long-range dependent?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(1), pages 66-88, January.
    19. Noor Fadhilah Ahmad Radi & Roslinazairimah Zakaria & Julia Piantadosi & John Boland & Wan Zawiah Wan Zin & Muhammad Az-zuhri Azman, 2017. "Generating Synthetic Rainfall Total Using Multivariate Skew-t and Checkerboard Copula of Maximum Entropy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(5), pages 1729-1744, March.
    20. Vitanov, Nikolay K. & Hoffmann, Norbert P. & Wernitz, Boris, 2014. "Nonlinear time series analysis of vibration data from a friction brake: SSA, PCA, and MFDFA," Chaos, Solitons & Fractals, Elsevier, vol. 69(C), pages 90-99.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3257-:d:169335. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.