Study On The Spatial Structure Of Soil Water-Salt And Crop Information And Their Correlation

The precision farming has been becoming the hot topic in the scope of agriculture technology, and the researches on the spatial variability of soil water-salt information and crop information are the technical support of implementing the precision farming. So in this thesis, the growing index of sunflower (Kang Di 105), soil water conten and soil EC are chosen as researching objectives, and the spatial variability of them and their correlation are researched. At the same time, the influencing coefficient method (ICM) is complemened and intrduced into the scope of soil water salt and crop information. The Cokriging is marked as CK and expressed by covariance function. The correlation of two variables is researched, and the coorelation of soil water content, soil EC and growing index of crop is also attempted researching.During the squaring stage, in 2003, the plant height and stem-diameter of sunflower have been measured. The soil water content, EC, the plant height and stem-diamete are regarded as regionalized variables, and the spatial variability of them are researched using the basic theory of geostatistics. Then product between the plant height and stem-diameter of sunflower is marked as the integrated index and regarded as primary variable. Choosing water conter and EC as secondary variable, the integrated index of sunflower is estimated using the three variables CK method that is in the form of covariance function. At the same time, the soil water content and EC is chosen as secondary variable respectively, the two estimation sets of the integrated index are obtained using the two variables CK method. Another estimation set is getted using Ordinary Kriging that can be markde as OK.The four estimation sets are analyzed and compared with the original set in different aspects. We can get the results that the estimation variance of CK is less than the estimation variance of OK, and estimation variance of three variables CK method is less than corresponding value of the two variables CK method. Using the method of Jacknife to compare the precision of the estimation sets, we find the Jacknife value of OK is less than the value of CK.Through statistically analyzing the four estimation sets and original set, we can get that the variance, standard deviation of the Cokriging estimation sets are more close to the corresponding values of the original set than the OK estimation set. But the coefficient of variation of the three variable CK is the most close to the coefficient of variation of the original set. So it indicates that increasing the number of secondary variable can increasing the information of the primary variable and can depict the spatial variability of the primary variable minutely. The results of the thesis are consistent with the results of Yates and Warrick (1987).