Study On Spatial Variability And Relationship Of Soil Arsenic And Soil Nitrogen

Soil is the most basic producting means of agricultural production, the soil quality information is the basis of soil ecological protecting and repairing work, the content of soil nutrients andpollutantsare important index of soil quality. In Zengcheng District of Guangzhou as the study area, on the basis of farmland productivity survey results, selecting 117 samples data, through different interpolation methods on spatial variability of soil arsenic and soil total nitrogen,and study on their relationships.The majoy contents and conclusions of study were as follows:(1)Through mathematical statistical analysis of 117 soil samples data obtained the distribution of soil arsenic and soil total nitrogen content varied widely in Zengcheng District.The variation coefficient of soil total nitrogen was 38.97%,which belonged to medium variation, look from partial degrees,although the valueis bigger than zero butis small, its distribution is symmetrical; the variation coefficient of soil arsenic was 84.41%, which belongs to strong variation, look from the partial degrees, soil arsenic have larger deviation, its distribution is deviateto the right.(2) For making spatial interpolation of soil arsenic, compared with the ordinary kriging, the RBF neural network performed better in terms of fitting ability and predicting precision.(3) The range of soil arsenic content are mainly distributed in 0-15 mg/kg, soil arsenic content in northeast and south of Zengcheng Districtis higher, and tends to gradually reduce from northeast to southwest, thecontentin western is low.The higher soil arsenic content(9-15mg/kg) mainly distributed in paitan town, zhengguo town, zengjiang streets, the northeastern of licheng streets, central and southern of shitan town and southern of xintang town, and the lower soil arsenic content(0-9 mg/kg) mainly distributed in zhongxin town, zhucun streets, southwest of lichen streets, northeast of shitan town and northern of xintang town.(4) In view of fitting ability and predicting precision, RBF neural network shows some advantages over the ordinary kriging for making spatial interpolation of soil total nitrogen.(5) High-level region of soil total nitrogen content(1-2.5g/kg) mainly distributed in xintang town, the westernof shitan town, zhucun streets,central and southern of paitan town, and since the middle spread out two direction shows the tendency of gradually reduce,the mid-level region of soil total nitrogen content(0.75-1g/kg) was found in paitan town, licheng streets and the easten of shitan town,and the low-level region of soil total nitrogen content(0-0.75g/kg) mainly distributed in zhongxin town, xiaolou town and zengjiang streets.(6) Both soil arsenic and soil total nitrogen contents in the brushland, forestland, orchard, cropland, dryland, backyard trended to increase, and the soil total nitrogen was highly correlated to soil arsenic with the correlation coefficient of 0.987 indifferent land use types. This correlation not only illustrates the soil arsenic and soil nitrogen are greatly influenced by human activities,but also illustrates that there are significantassociations between soil arsenic and soil nitrogen in the study area.(7) Using soil arsenic as a covariate to make co-kriging interpolation of soil nitrogen, the co-kriging resulted in higher fitting ability and predicting precision than ordinary kriging and RBF neural network, suggesting that there are significant associations between soil arsenic and soil nitrogen, and the soil arsenic content affects the spatial variation of soil nitrogen.