| 西安市农用地土壤有机质空间变异特征 |
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| 引用本文： | 孙喜军,邓睿,吕爽,高莹,蔡苗,缑巧红,赵娟.西安市农用地土壤有机质空间变异特征[J].中国农学通报,2022,38(35):43-53. |
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| 作者姓名： | 孙喜军 邓睿 吕爽 高莹 蔡苗 缑巧红 赵娟 |
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| 作者单位： | 1.西安市农业技术推广中心，西安 710061;2.西安市高陵区农业技术推广中心，西安 710200;3.咸阳职业技术学院，陕西咸阳 712000;4.西安市临潼区农技推广服务中心，西安 710600 |
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| 基金项目： | 西安市科技局农业技术研发项目“西安市设施菜地土壤次生盐渍化现状及防控关键技术研究”(20NYYF0044);咸阳职业技术学院科研基金项目“4种改良剂防治设施土壤次生盐渍化效果研究”(2020KJC01);咸阳职业技术学院2021年度博士科研基金项目“国家中心城市近郊设施菜地土壤次生盐渍化现状及防控关键技术研究-以西安市为例”(2021BK03) |
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| 摘 要： | 准确识别区域农用地土壤有机质(Soil organic matter，SOM)空间变异规律及其影响因素，能为农业生产活动提供一定的科学指导。该研究以西安市为例，利用地统计学与GIS技术相结合的方法，对农用地SOM空间变异特征及其影响因素进行了分析。结果表明：研究区SOM平均含量为17.07±4.37 g/kg，变异系数为25.60%；SOM半方差函数的最佳理论模型为指数模型，模型块金系数为49.83%，说明研究区SOM空间变异受到结构性因素和随机性因素的双重影响；以东北—西南向为轴线，研究区SOM含量的空间分布大体呈现中部高而东西低的斑块状分布趋势；研究区SOM含量受土壤类型、土壤质地、地貌类型和土地利用类型的影响，并与pH、海拔存在显著的负相关关系。总体来看，研究区SOM丰缺等级属于中等水平，且不同区县农用地SOM含量极值差异较为明显，实际农业生产活动中需分区进行差异化施肥管理。
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| 关 键 词： | 地统计学 GIS 土壤有机质 空间变异 土壤类型 土壤质地 地貌类型 土地利用类型 |
| 收稿时间： | 2022-07-10 |
Spatial Variability Characteristics of Farmland Soil Organic Matter in Xi'an |
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| SUN Xijun,DENG Rui,LV Shuang,GAO Ying,CAI Miao,GOU Qiaohong,ZHAO Juan.Spatial Variability Characteristics of Farmland Soil Organic Matter in Xi'an[J].Chinese Agricultural Science Bulletin,2022,38(35):43-53. |
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| Authors: | SUN Xijun DENG Rui LV Shuang GAO Ying CAI Miao GOU Qiaohong ZHAO Juan |
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| Institution: | 1.Xi’an Agricultural Technology Extension Center, Xi’an 710061;2.Xi’an Gaoling District Agricultural Technology Extension Center, Xi’an 710200;3.Xianyang Vocational Technical College, Xianyang, Shaanxi 712000;4.Xi’an Lintong Agricultural Technology Extension Service Center, Xi’an 710600 |
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| Abstract: | Accurately identifying the spatial variability of soil organic matter (SOM) and its affecting factors in regional farmland can provide guidance for agricultural production. Taking Xi’an as an example, the spatial variability of farmland SOM and its affecting factors were analyzed by using geostatistics and GIS technology. The results showed that the average content of SOM in the study area was 17.07±4.37 g/kg, and the coefficient of variation (CV) was 25.60%. The best theoretical model of SOM semi-variance function was the exponential model, and the nugget coefficient of this model was 49.83%, which indicated that SOM spatial variability in the study area was affected by the dual effects of structure factors and random factors. Taking the northeast—southwest direction as the axis, the spatial distribution of SOM content in the study area generally showed a distribution trend of higher in the middle and lower in the east and west. The SOM content in the study area was affected by soil type, soil texture, landform type and land use type. Meanwhile, SOM content had significantly negative correlations with pH and altitude. Overall, the SOM abundance level in the study area was moderate, and the difference in SOM content of farmland soil in different counties was obvious. In agricultural production, differential fertilization management needs to be carried out in different regions. |
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| Keywords: | geostatistics GIS soil organic matter spatial variability soil type soil texture landform type land use type |
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