| With the continuous improvement of the level of agricultural intensification and the rapid development of economy,China’s cultivated land is in the long-term high-intensity and overload use,which leads to serious degradation of soil fertility and cultivated land quality,high damage to the quality and safety of ecological environment,and causes a series of ecological environment and public safety and health problems.At present,most of the soil fertility indexes are studied in a single scale,and the evaluation methods of cultivated land quality in different departments and periods are also different.In order to better serve the cultivated land quality evaluation and reveal the variation law of soil fertility indexes in time and space.Based on the semi variance function model of spatial variation of soil fertility index under different sampling density,this paper established a nested model,and explored the spatiotemporal evolution law and driving factors of soil fertility index in the study area based on the nested model In order to evaluate the quality of cultivated land in the study area and establish a system to realize automatic evaluation,the method system of cultivated land quality grade evaluation at county level was established.The following main conclusions are obtained:(1)Under different sampling densities,the average values of soil organic matter,total nitrogen,available phosphorus and available potassium were 17.31～21.72g/kg,1.21～1.52g/kg,94.56～150.17mg/kg and 212.88～310.42mg/kg,respectively.Considering RMSE,R2 and PE,the nested model method is better than the ordinary interpolation method.The prediction of soil available potassium is suitable for small-scale sampling density,and the prediction of soil organic matter,total nitrogen and available phosphorus is the best in medium scale sampling density.At the same time,before making the actual sampling scheme,we should fully grasp the variation characteristics of each index,apply the historical data and combine the prediction accuracy and efficiency of each index to make the sampling scheme(2)The average value of available phosphorus content in soil increased 74.59mg/kg in the 10 years from 2008 to 2018,with the largest increase of 313.01%,followed by total nitrogen and available potassium,with the average content increasing by 0.48g/kg and 111.68mg/kg,with an increase of 65.75%and 60.74%respectively;The growth rate of soil organic matter was 43.94%and the average content increased by 5.22g/kg.The soil use type,soil type and elevation significantly affected the soil organic matter content,the significance values were 0.026,0.004 and 0.046,respectively,among which the influence of altitude on soil organic matter content was very significant;The soil types and elevation significantly affected the total nitrogen content of soil,the significance values were 0.003 and 0.038,among which the influence of altitude on the total nitrogen content of soil was very significant,only the altitude significantly affected the soil available phosphorus content,the significance value was 0.044 respectively;The three factors had no significant effect on available potassium.(3)Through the verification of cultivated land quality grade,the average cultivated land quality grade of the research area is 3.43.Among them,the vast majority of cultivated land quality grade in the region is grade 6 and above,accounting for 94.34%of the total cultivated land area of the research area.The cultivated land quality grade is below grade 7 mainly distributed in the northern mountainous areas and some eastern areas,with the cultivated land area accounting for less than 2%.Through the yield verification,the cultivated land quality grade and yield in the empirical area are positively correlated.The evaluation method system can basically reflect the cultivated land quality level.Based on GIS,the cultivated land quality database of Pinggu District is established,and a seamless and seamless coupling system of County Cultivated Land Quality Investigation and evaluation is developed.The system can realize the functions of basic database management,query and dynamic update,farmland quality evaluation,and spatial prediction of cultivated land information.Figure[48]table[30]reference[78]... |
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