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Quantitative Analysis of Annual Precipitation in Extreme Precipitation Areas

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DOI: 10.23977/erej.2022.060211 | Downloads: 3 | Views: 62


Hanzhi Zhang 1, Wenjing Zhao 1


1 School of Business, Xi’an International Studies University, Xi’an 710128, China

Corresponding Author

Hanzhi Zhang


This paper analyzed the characteristics of annual changes in areas with extreme rainfall to better understand the precipitation patterns. Trend analysis, cycle analysis and mutation analysis were carried out on the historical precipitation of Zhengzhou stations, so as to describe and analyze the annual variation characteristics of precipitation in Zhengzhou. The trend analysis uses R/S analysis method to show that the precipitation in Zhengzhou shows a strong anti-continuous trend. The cycle analysis adopts the Morlet wavelet analysis method, and the annual average precipitation shows the law of 6a as the first main cycle and 10a as the second main cycle. Mutation analysis was performed by Mann-Kendall method, which showed that the precipitation sequence in Zhengzhou had a mutation during 2013 and that the mutation was significant. The interannual change in precipitation maintains a significant upward trend after a brief downtrend at the breakout point.


Trend Analysis, Quantitative Analysis of Precipitation, Morlet Wavelet Analysis


Hanzhi Zhang, Wenjing Zhao, Quantitative Analysis of Annual Precipitation in Extreme Precipitation Areas. Environment, Resource and Ecology Journal (2022) Vol. 6: 90-94. DOI:


[1] Li Xiaodong, Wang Yongqiang, Liu Wan, Xu Jijun, Qu Simin. Analysis of the temporal and spatial evolution characteristics of precipitation in the typical area of the Three Rivers Source from 1967 to 2019 [J/OL]. Journal of Yangtze River Scientific Research Institute: 1-10.Fangfang. Research on power load forecasting based on Improved BP neural network [D]. Harbin Institute of Technology, 2011.
[2] Wang Wei. Enlightenment on the innovation of urban governance caused by climate risk [J]. Urban Management and Technology, 2021, 22(05): 28-31. Ma Kunlong. Short term distributed load forecasting method based on big data [D]. Changsha: Hunan University, 2014.
[3] Ye Minghua, Chen Kang. Urban catastrophe risk: meteorological characteristics, loss status and management countermeasure optimization——Taking Zhengzhou "July 20" heavy rain-storm and typhoon "fireworks" as an example [J]. Shanghai Insurance, 2021(08)): 18-22.
[4] Sun Jie, Xu Yang, Chen Zhenghong, Wang Kai. Analysis of the characteristics of precipita-tion changes in Central China in the past 45 years [J]. Resources and Environment in the Yangtze River Basin, 2010, 19(S1): 45-51.
[5] Baole Erqimuge. Analysis on the characteristics of continuous non-precipitation diurnal variation in the desert grassland of Inner Mongolia from 1960 to 2020 [J/OL]. Arid area geography: 1-15.

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