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The interval days statistical diagnostic model of soil moisture.

LI Jing-ya1, HOU Xian-da2, HOU Yan-lin1,2, LIU Shu-tian1,2*, ZHENG Hong-yan1, MI Chang-hong1, HUANG Zhi-ping1, DING Jian1   

  1. (1Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China; 2Key Laboratory of Environment Change and Resources Use in Beibu Gulf (Guangxi Teachers Education University); Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation (Guangxi Teachers Education University), Nanning 530001, China)
  • Online:2017-12-10 Published:2017-12-10

Abstract:

The principle and modeling method of the interval days statistical diagnostic model of soil moisture were introduced. Models were established by the data of 87 monitoring sites in 23 counties from 7 provinces during the period of 2012-2014, and validated by the data of 2015. The results showed that the accuracy of diagnosis and prediction of the interval days statistical diagnostic model was high, reaching up to 90%. Interval days statistics diagnostic model had a high diagnosis and prediction rate because of the addition of the interval days variable, which effectively solved the problem of unfixed interval. The daily time series model could achieve daily prediction of soil moisture. In conclusion, the interval days statistical diagnostic model can be used alone as a soil moisture diagnosis model.
 

Key words: Qinling Mountains, vulnerability, human disturbance., landscape pattern