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Ratio statistical diagnostic model of soil moisture.

ZHENG Hong-yan1, DING Jian1, HOU Xian-da2, HOU Yan-lin1,2*, MI Chang-hong1, HUANG Zhi-ping1, LIU Shu-tian1,2, WANG Shuo-jin2   

  1. (1Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China; Key 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 ratio statistical diagnostic model of soil moisture based on time-period precipitation and initial soil water content were introduced. Models were established by the data of 87 monitoring sites in 23 counties in 7 provinces during 2012-2014, and validated by the data of 2015. The results showed that the ratio statistical diagnostic model had high qualification rate (>80%) in diagnosis and prediction. The main reason for the high qualification rate of diagnosis and prediction was that the model parameters were the results of data mining, not determined by human. Daily time series model can predict daily soil water. The results indicated that the ratio statistical diagnostic model could be used alone as a soil moisture diagnosis model.
 

Key words: ecological system, land-based pollution, spatial distribution, Jiaozhou Bay., nutrient