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北京市顺义区浅层土壤硝态氮的空间变异特征分析
引用本文:陆红娜,唐泽军,冯绍元,张自军,赵亮.北京市顺义区浅层土壤硝态氮的空间变异特征分析[J].环境科学学报,2010,30(12):2563-2570.
作者姓名:陆红娜  唐泽军  冯绍元  张自军  赵亮
作者单位:1. 中国农业大学水利与土木工程学院,北京,100083
2. 河北工程大学水利水电学院,邯郸,056021
基金项目:北京市科技计划(No. D07050601510703-3);国家水体污染控制与治理科技重大专项(No. 2008ZX07209-002-01);水利部公益基金项目(No. 200901083)
摘    要:顺义是北京市的主要水源地和农业生产基地,研究氮素在顺义区土壤中的分布累积及空间变异情况,对于了解顺义区的土壤潜在污染,指导农业生产,预防面源污染等具有重要作用.因此,本研究应用传统统计学方法和基于GIS的地统计学法研究了顺义区不同地点各土层土壤中硝态氮的空间分布特征.结果发现,地统计分析过程中,在考虑各向异性和趋势效应的情况下,各土层土壤硝态氮含量均具有空间相关性,理论变异模型主要为球状模型和指数模型.同时,选用普通Kriging插值法得到了各土层土壤硝态氮的空间分布图,并对其空间分布特征进行了分析.结果表明,研究区不同土层硝态氮空间分布状况各异,潮白河东部土壤硝态氮含量高于潮白河西部.

关 键 词:硝态氮  空间变异  地统计学法
收稿时间:3/31/2010 8:24:37 PM
修稿时间:8/5/2010 12:05:41 AM

Spatial variability of nitrate content in different soil layers in the Shunyi District of Beijing
LU Hongn,TANG Zejun,FENG Shaoyuan,ZHANG Zijun and ZHAO Liang.Spatial variability of nitrate content in different soil layers in the Shunyi District of Beijing[J].Acta Scientiae Circumstantiae,2010,30(12):2563-2570.
Authors:LU Hongn  TANG Zejun  FENG Shaoyuan  ZHANG Zijun and ZHAO Liang
Institution:College of Water Conservancy & Civil Engineering, China Agricultural University, Beijing 100083,College of Water Conservancy & Civil Engineering, China Agricultural University, Beijing 100083,College of Water Conservancy & Civil Engineering, China Agricultural University, Beijing 100083,College of Water Conservancy & Hydropower, Hebei University of Engineering, Handan 056021 and College of Water Conservancy & Civil Engineering, China Agricultural University, Beijing 100083
Abstract:Shunyi is an important water resource and agricultural production base of Beijing. Studies on the nitrogen accumulation in soil and its spatial variability are significant to understand the potential pollution in soil, and guide agricultural practice to prevent non-point source pollution. Traditional statistics and geostatistics based on GIS were used to analyze the spatial distribution of nitrogen in different soil layers. Considering the anisotropy and trend effects, the nitrate content in different soil layers are all spatially correlated. The theoretical variogram models of spherical and exponential forms fit the data well. Spatial distribution maps of nitrate content for the research area were created by ordinary Kriging interpolation. The results showed that the nitrate had a strong variability among the different layers, and in general, the nitrate content in the east part is higher than that in the west.
Keywords:nitrate  spatial variability  geostatistics
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