PI模型在东北松嫩黑土区土壤生产力评价中的应用  

Applied PI Model in Soil Productivity Assessment of Song Nen Black Soil Region in Northeast China

作　　者：段兴武[1] 谢云[1] 张玉平[1] 刘冰[1] 

机构地区：[1]地表过程与资源生态国家重点实验室北京师范大学地理学与遥感科学学院,北京100875

出　　处：《中国农学通报》2010年第8期179-188,共10页Chinese Agricultural Science Bulletin

基　　金：国家自然科学基金项目"维持可持续土地生产力的定量标准:容许土壤流失量"(40671111);国家重点基础研究发展规划项目"区域水土流失过程与趋势分析"(2007CB407203)

摘　　要：土壤生产力指数模型(Soil Productivity Index,简称PI)的简单实用性使其在国外土壤生产力评价及侵蚀对土壤生产力的影响评价等方面获得了广泛应用,但在中国国内却缺少该模型的系统性介绍和验证性研究。因此,论文在系统介绍PI模型的基础上,以东北松嫩黑土区为研究区,利用研究区17个土壤剖面理化性质数据和作物产量调查数据,比较分析了表土评价法(CI),原PI模型以及根据研究区土壤特性订正过的PI模型(BPI)对土壤生产力的评价效果。结果表明:(1)CI法生产力指数差异小,不易将土壤生产力水平进行分异;PI和BPI模型生产力指数差异大,容易将土壤生产力水平进行分异;(2)3种模型生产力指数与正常年景玉米产量的线性回归结果,BPI模型最好(R2=0.6774,P<0.01),其次是PI模型(R2=0.3357,P<0.05),CI模型较差(R2=0.0865),未通过显著性检验(P>0.05);(3)PI模型对于土壤有机质含量较低的土壤生产力水平出现高估,BPI由于引入有机质含量指标,评估效果明显改善。总体而言,PI模型将一定厚度的土体作为对象综合评价土壤生产力,效果明显优于表土评价法,但在具体地区应用时,应根据当地土壤生产力影响因子的重要性,选择适当指标进行修订。东北地区有机质对作物生长十分重要,引入该指标后明显改善了PI模型对土壤生产力的评价效果。Since its simplicity and practicability, Soil productivity index model （PI for short） have found wide application in soil productivity assessment and assessment of long-term changes of soil productivity due to erosion in overseas. But, now there are no systematic report and verification research for this model in China. So, base on the systematic introduction of PI, the paper take Song Nen black soil region in Northeast China as study area, seventeen soil profiles in North-East black soil region were chosen, three different mod- els： Surface soil layer estimate （CI）, Productivity index model （P/） and modified productivity index model （BPI） were used based on physico-chemical properties of soil profile; finally, simulated results were compared with crop yield of these soil profiles, the results show： （1）the discrepancy of calculated index was close for CI model, it can not help to distinguish soil productivity between different soil; but the discrepancy were obvious for PI and BPI model, it is good for distinguishing soil productivity between different soil. （2） Correlation between productivity index and corn yield in common years were analyzed, The highest Determination coefficient with R^2=0.6774（P 〈 0.01） was appeared in BPI model, followed by PI model with R^2=0.3285（P 〈0.05）, the lowest was appeared in CI model （P 〉 0.05）. （3） PI model over-estimate the result for those soil with low organic content, after import organic factor in to the model, BPI got a better estimation for black soil. In conclusion, PI model take upper 100cm horizon soil as estimated object of soil productivity, the estimated accuracy is better than CI model. If organic factor was considered, the BPI model got a better estima- tion than PI model.

关 键 词：PI模型 土壤生产力 松嫩黑土区 

分 类 号：S158[农业科学—土壤学] S181[农业科学—农业基础科学]