首页|高密市农田土壤养分空间变异特征研究

高密市农田土壤养分空间变异特征研究

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以高密市为例,利用GIS和地统计学方法在县域的尺度上分析土壤有机质、全氮、碱解氮、有效磷、速效钾、有效锰、有效铜、有效锌、有效硼9种养分的空间变异情况,利用克里格插值分析土壤养分的空间分布格局。结果表明,有效磷变异系数最大为48.80%,有机质变异系数最小为21.76%,变异系数由大到小依次为有效磷〉有效锌〉速效钾〉有效铜〉有效硼〉有效锰〉碱解氮〉全氮〉有机质。各土壤养分都具有良好的半方差结构,除了有效锰符合线性模型以外,其他养分均符合指数模型。速效钾、有效铜、有效锌具有强烈的空间自相关性;有机质、全氮、碱解氮、有效磷、有效锰、有效硼具有中等强度的空间自相关性,自相关程度速效钾〉有效铜〉有效锌〉有效硼〉全氮〉碱解氮〉有机质〉有效磷〉有效锰。在空间自相关范围上,有效硼最大为28716 m,有效铜最小为1410 m。微量元素锰、硼在空间分布上呈现出明显的规律性,锰呈现出从北到南逐渐增加的趋势,而硼含量则是从北到南逐渐减小;有机质、全氮、碱解氮三种元素呈现出相似的空间分布格局;有效铜、有效锌没有明显的规律性;有效磷、速效钾高值区呈块状零星分布。该研究揭示了高密市土壤养分的空间分布规律,对于实施精准农业和耕地的可持续利用具有积极意义。
Spatial Variability of Soil Nutrients of Cultivated Land in Gaomi Area
Geostatistics combining with GIS was applied to analyze the spatial variability and spatial distribution of soil nutrients in Gaomi at county scale,including 9 soil nutrients of SOM,AN(alkaline hydrolyzing nitrogen),TN,available K,available P,Mn,Cu,Zn and B.The results showed that the variation coefficient of soil nutrients followed the order of P Zn K Cu B Mn AN TN SOM.P had the highest variation coefficient of 48.80%,while SOM had the lowest of 21.76%.The semivariograms of soil nutrients were best described by exponential model,except for that of Mn,which was best fitted by liner model.K,Cu and Zn had significant spatial self-correlation,and other nutrients had medium spatial self-correlation.The spatial self-correlation degree ordered as K Cu Zn B TN AN B SOM P Mn.The spatial correlation range of B was the highest of 28716 meters,and that of available Cu was the lowest of 1410 meters.Mn and B showed an obvious regularity in spatial distribution,with the content of Mn increased gradually from north to south,while content of B decreased gradually from north to south in the study area.SOM,TN and alkali-hydrolysable nitrogen showed a similar spatial pattern,Cu and Zn had no significant geographical trends,and the high value areas of K and P spatial distributed sporadically.This study revealed the spatial distribution of soil nutrients in Gaomi,which had a positive significance for precision agriculture and sustainable use of land resource.

GeostatisticsSoil nutrientsSpatial variabilityGISGaomi.

赵倩倩、赵庚星、董超、李文璐

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山东农业大学资源与环境学院,山东泰安271018

地统计学 土壤养分 空间变异 GIS 高密市

国家自然科学基金国家级“星火计划”重点项目

405711602007EA740002

2012

土壤通报
中国土壤学会

土壤通报

CSTPCDCSCD北大核心
影响因子:0.818
ISSN:0564-3945
年,卷(期):2012.43(3)
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