A Study On The Relationship Between The Spatial Variability Of Soil Chemical Characteristics And The Cotton Growth

The study researched the relationship between the spatial variability of some chemical characteristics and cotton growth of saline anthropogenic-alluvial soil by the method of traditional statistics and geostatistics. The analysis results showed: the data of soil chemical characteristics accorded with normal probability distribution, and reasonable sampling numbers were given under certain precision and credible level. The spatial variability of the available N and available P was stronger than solute salt and available K, and of total N was stronger than total P and total K of soil surface layer at horizontal direction; At vertical direction, the spatial variability of available nitrogen and phosphorous of soil was very clear, their contents were gradually decreased with increase of sampling depth, especially available phosphorous, but available potassium and solute salt of soil had no clear vertical variability. The spatial variability of the total salt and the available nutrient of soil were decreased with the growth of cotton, and their semi-variogram maps and contour maps were presented. The relative analysis of soil chemical characteristics and cotton yield and soil chemical characteristics showed: soil chemical characteristics by themselves had correlation, cotton yield and soil chemical characteristics had different correlation too. For example, the correlation of solute salt ,available potassium of soil and cotton yield was outstanding negative, and of organic matter,available nitrogen and cotton yield was outstanding positive. The correlation of available nitrogen and solute salt,available potassium was outstanding negative, and available phosphorous was outstanding positive ; and the correlation of available potassium and solute salt was outstanding positive. The study achieved simulated precision recommendation fertilization of available nitrogen and available phosphorous with Geographical Information System (GIS) and Computer Recommendation Fertilizer System (CRFS). The study provided the basic data and theoretical basis for realizing precise management of nutrient, improving the saline soil and increasing experimental effectiveness.