| Luancheng station area is the most representative high-yielding intensive agriculturalarea and important commodity grain base in North China, the quantity of water loss is themost severe. Since1970s, the development of agricultural production relys onover-exploitating a large number of groundwater. This paper analyzes time statisticalproperties、 time autocorrelation、 temporal and spatial variation characteristics and itsinfluencing factors of soil moisture in Luancheng station from time and depth dimensionsbased on geostatistical methods, in order to provide a frame of reference for the efficient useof soil moisture in the area. The main results are as follows:1. Calculated monthly average and coefficient of variation in use of defining equationof the mean and variation in geostatistics, and drew curves of the resulting statisticalparameters using software origin. On this basis, through analyzed diversification of statisticalparameters with time t and depth h, indicating: variation of soil moisture during the yeargenerally showing "∽" type, its value is the most unstable between April and June, with thedepth h increases, soil moisture generally showing a trend of decreasing, stability is gettingbetter too.2. Established the soil moisture time autocorrelation analysis model in use of correlationanalysis theory, analyzed correlation of soil moisture using software spss, and fitting theresulting autocorrelation coefficients r(△t), got soil moisture time autocorrelation functionfitting curve and its residuals of different depths. And through its comparative analysis, foundthat the greater the depth h, the greater soil moisture autocorrelation time scales, the degree ofthe autocorrelation function of curve fitting better, the scale of residuals is smaller.3. Drew different years and years of soil moisture time-depth contour map in the surfersoftware platform, through comprehensive comparison, analyzed and discussed the trend andthe main influencing factors of soil moisture for many years. |
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