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北京市北运河流域耕地土壤性质空间变异性

张瑞,戴伟**,庞欢,邹建美   

  1. (北京林业大学林学院, 北京 100083)
  • 出版日期:2014-12-10 发布日期:2014-12-10

Spatial variations in soil properties of cropland in North Canal basin in Beijing.

ZHANG Rui, DAI Wei**, PANG Huan, ZOU Jian-mei   

  1. (College of Forestry, Beijing Forestry University, Beijing 100083, China)
  • Online:2014-12-10 Published:2014-12-10

摘要:

运用ArcGIS和地统计学相结合的方法研究了北运河流域0~50 cm土壤的pH、容重、有机质、有效磷和全氮5种肥力参数的空间分布特征。结果表明:pH值、容重、有机质、全氮的变异系数在6%~22%,属弱中等变异水平,有效磷变异系数最大,为68%;通过半方差函数分析,5种参数变异函数的曲线理论模型都符合高斯模型,且在一定间距内均存在空间相关性,土壤pH值和容重表现强烈的空间自相关性,其空间变异主要是由结构性因素引起。土壤有机质、全氮和有效磷空间相关性中等,是由结构性因素和随机性因素共同作用的。采用普通克立格方法进行最优内插,绘制了养分含量分布图,统计了分级土地面积,并对其空间变异进行了分析。研究结果对于评价北运河流域土壤养分空间变异规律和动态变化有一定的实践意义,可应用于精准农业。

 

关键词: 冬小麦, WOFOST作物模型, 减产风险

Abstract: Spatial variations in soil fertility parameters of the soil (0-50 cm) of cropland in the North Canal basin of Beijing were analyzed using geo-statistics and geographical information system (GIS). Soil fertility parameters included pH, bulk density, organic matter, total nitrogen and available phosphorus. The results revealed a significant spatial variation in the five soil fertility parameters. Available soil phosphorus had the largest coefficient of variation (68%). The coefficient of variation ranged from 6% to 22% for soil pH, bulk density, organic matter, and total nitrogen. The semi-variograms of the five soil fertility parameters were best described by the Gaussian model. Soil pH and bulk density had a relatively strong spatial correlation, which was caused by structural factor. In contrast, soil organic matter, total nitrogen and available phosphorus had moderate spatial correlations, which were related to both structural and random factors. Using a Kriging method, spatial distribution maps of the soil fertility parameters were made and the areas of graded lands were counted. Meanwhile, the spatial variations of soil fertility parameters were analyzed. We argue that the analysis of spatial patterns of soil fertility parameters in the North Canal basin is essential for precision agriculture.

Key words: WOFOST crop model, winter wheat, yield reduction risk