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A multifractal cross-correlation investigation into sensitivity and dependence of meteorological and hydrological droughts on precipitation and temperature

Author

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  • Farhang Rahmani

    (Islamic Azad University)

  • Mohammad Hadi Fattahi

    (Islamic Azad University)

Abstract

Several studies have been conducted on droughts, precipitation, and temperature, whereas none have addressed the underlying relationship between nonlinear dynamic properties and patterns of two main hydrological parameters, precipitation and temperature, and meteorological and hydrological droughts. Monthly datasets of Midlands in the UK between 1921 and 2019 were collected for analysis. Subsequent to apply a multifractal approach to attain the nonlinear features of the datasets, the relationship between two hydrological parameters and droughts was investigated through the cross-correlation technique. A similar process was performed to analyze the relationship between multifractal strength variations in time series of precipitation and temperature and droughts. The nonlinear dynamic results indicated that droughts (meteorological and hydrological) were substantially affected by precipitation than temperature. In other words, droughts were more sensitive to precipitation fluctuations than temperature fluctuations. Concerning temperature, meteorological, and hydrological droughts were dependent on the minimum and maximum temperatures ( $$T_{{{\text{min}}}}$$ T min and $$T_{{{\text{max}}}}$$ T max ), respectively. The correlation between precipitation and meteorological drought was more long-range persistence than precipitation and hydrological drought. Besides, the correlation between $$T_{{{\text{max}}}}$$ T max and droughts was more long-range persistence than $$T_{{{\text{min}}}}$$ T min and droughts. Analysis of nonlinear dynamic patterns proved that the multifractal strength of meteorological drought depended on the multifractal strength of precipitation and $$T_{{{\text{max}}}}$$ T max , whereas the multifractal strength of hydrological drought depended on the multifractal strength of the $$T_{{{\text{min}}}}$$ T min . The correlation between precipitation and drought indices exhibited more multifractal strength than temperature and drought indices. Finally, the pivotal role of maximum temperature on drought events was quite alerting due to global warming intensification.

Suggested Citation

  • Farhang Rahmani & Mohammad Hadi Fattahi, 2021. "A multifractal cross-correlation investigation into sensitivity and dependence of meteorological and hydrological droughts on precipitation and temperature," 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. 109(3), pages 2197-2219, December.
    • Handle: RePEc:spr:nathaz:v:109:y:2021:i:3:d:10.1007_s11069-021-04916-1
    DOI: 10.1007/s11069-021-04916-1
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    2. Fernandes, Leonardo H.S. & Silva, José W.L. & de Araujo, Fernando H.A., 2022. "Multifractal risk measures by Macroeconophysics perspective: The case of Brazilian inflation dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
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    4. Zhan, Cun & Liang, Chuan & Zhao, Lu & Jiang, Shouzheng & Niu, Kaijie & Zhang, Yaling, 2023. "Multifractal characteristics of multiscale drought in the Yellow River Basin, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).

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