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Spatial Distribution and Temporal Trends in Precipitation Concentration Indices for the Southwest China

Author

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  • Peng Shi
  • Miao Wu
  • Simin Qu
  • Peng Jiang
  • Xueyuan Qiao
  • Xi Chen
  • Mi Zhou
  • Zhicai Zhang

Abstract

Changes in the spatiotemporal patterns of precipitation have great impacts on drought/flood risk and utilization of water resources. In this study, we presented the results of a comparative analysis of spatial-temporal variability of precipitation in the Southwest China. The analysis investigated the trends of annual precipitation and explored the changes of two indices: the precipitation concentration index (PCI) and the concentration index (CI) which are designed for measuring seasonality and daily heterogeneity, respectively. The trends of annual precipitation and CI were tested by the Mann-Kendall method. The results show a significant seasonality of the rainfall distribution and very inhomogeneous temporal distribution of the daily rainfall in the study area. Positive trends in the CI were found at most stations, although most of them were not statistically significant. To detect the futures trends of precipitation in the study area, Hurst’s rescaled range (R/S) analysis was introduced and the corresponding Hurst Exponent was estimated. The results suggested that some drought hazards will happen in the intersection of Sichuan, Guizhou and Yunnan, and the west part of Sichuan, the north part of Chongqing and the middle part of Yunnan are under the risk of flood in the future. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:11:p:3941-3955
    DOI: 10.1007/s11269-015-1038-3
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    2. 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.
    3. Lo Magno, Giovanni L. & Ferrante, Mauro & De Cantis, Stefano, 2017. "A new index for measuring seasonality: A transportation cost approach," Mathematical Social Sciences, Elsevier, vol. 88(C), pages 55-65.
    4. 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.
    5. Cheng, Minghan & Jiao, Xiyun & Jin, Xiuliang & Li, Binbin & Liu, Kaihua & Shi, Lei, 2021. "Satellite time series data reveal interannual and seasonal spatiotemporal evapotranspiration patterns in China in response to effect factors," Agricultural Water Management, Elsevier, vol. 255(C).
    6. Shen, Chenhua, 2019. "The influence of a scaling exponent on ρDCCA: A spatial cross-correlation pattern of precipitation records over eastern China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 579-590.

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