| Tongliang county is located in the west of Chongqing, the main grain producing area. Recently, with the human irrational utilization of land, causing the soil physical, chemical and biological properties changed greatly. Especially in different regions and utilization ways,the soil nutrient is largely different, those causing the soil productivity changed. The study about soil fertility of purple hilly area in Tongliang county of Chongqing, in the application of geographic information system, using the Delphi method to select9factors and using AHP judginent matrix, to determine weight, and then using fuzzy mathematical method to fit membership function, create database, through the county land resources system calculation of cultivated land fertility index, divide farmland grade, for the Tongliang county soil and fertilizer utilization and provide the scientific basis. The Conclusions is:(1)The preliminary analysis of soil nutrient. In the study area7335sample point of5indexes descriptive statistical analysis, the results showed:the study of pH was neutral to slightly acidic, soil organic matter, nitrogen, phosphorus and potassium in the range of2.9～49.6g·kg-1、21～200mg·kg-1、0.3～30mg·kg-1、14～200mg·kg-1. The soil nutrient content in a deficiency condition, research area of soil nutrient variation coefficient were0.18～0.68, moderate variation in intensity. The coefficient of variation was P>OM> K> N> pH.(2)The chemical properties of soil in semi variogram fitting. Application of GS+9.0software in variogram fitting semi variance model, to research the soil pH, organic matter, nitrogen, available potassium and available phosphorus of soil fertility has important influence factor for half the variance analysis and study on the spatial variability of soil organic matter and available P, in which selection index model, pH, alkaline hydrolysis nitrogen linear model, available potassium. The nutrient content of spatial autocorrelation distance is greater than the sampling interval, thus indicating that the soil nutrient in certain areas within the existing spatial correlation. The results showed:pH and organic matter of gold than [C0/(C+C0)] in25%～75%, belong to moderate spatial correlation; available nitrogen and available potassium gold ratio greater than75%, the spatial correlation is very weak, that are influenced by random factors such as (the experimental error, fertilization, management level and so on) a greater impact; available phosphorus a strong correlation.(3) Using inverse distance weighted interpolation method, combining with two Soil Census nutrient classification standard, rendering of each soil nutrient spatial interpolation maps, and analyzes the different levels of nutrient content and spatial distribution trend. From the spatial distribution pattern of the study area, most nutrients in bulk distribution. From the classification of the soil nutrient status, nutrient content, the distribution has very big difference, besides the effective phosphorus content is low, other nutrients in medium level.(4) Soil fertility evaluation. The results showed, the area and percentage of the first, second, third, fourth and fifth grade were6966.87hm2,11.27%,14734.98hm2,23.83%,18695.64hm2,30.23%,14868.08hm2,24.04%,6573.91hm2,10.63%. The overall level of soil fertility in the third grade, followed by second and fourth. Further analysis of the soil nutrient fertility on spatial distribution of land, divided into paddy field and dry land, respectively on the elevation, topography, soil type, texture and parent material types for statistical analysis, and the mapping of the fertility degree distribution table, the results showed that:elevation in500m following, landform is located in the low hills mountain area, gray brown purple mud paddy soil, sandy loam and sandy loam region of fertility levels, showed a higher level.(5) Field data validation. Field data validation to ensure the accuracy of evaluation results and practical, according to the5different soil fertility levels, choose expert validation, field surveys and other means of plots for verification. Validation results and fertility evaluation results are completely consistent, so the results and the reality of good agreement. |
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