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运城市夹马口引黄灌区土壤养分空间变异特征 被引量:5

Spatial variation of soil nutrients in the Jiamakou Yellow River irrigation area,Yuncheng City
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摘要 以山西省运城市夹马口引黄灌区为研究区域,在灌区进行田间取样,结合地统计学与Kriging插值方法分析灌区农田有机质、全氮、碱解氮、有效磷、速效钾的空间分布特征。研究结果表明,灌区土壤有机质、全氮空间变异主要受结构性因素的影响;碱解氮、有效磷、速效钾空间变异受结构性因素、随机性因素的共同影响。土壤有效磷呈斑块状分布,存在局部富集或缺失情况;有机质含量在灌区西南部平坦地区、中部引黄灌区干渠中下游冲积区相对较高,土壤全氮、碱解氮具有相似分布。灌区土壤有效磷、速效钾养分等级较高,土壤碱解氮养分等级中等,土壤有机质、全氮养分等级较低。交叉验证表明,普通克里格插值能较准确地预测灌区的土壤养分的空间变化,其相关系数较高、稳定性较好,为灌区精准施肥提供建议。 The spatial nutrients distribution of organic matter(TOM),total nitrogen(TN),alkali-hydrolyzable nitrogen(AN),available phosphorous(AP),quick-acting potassium(AK)in the Jiamakou irrigation area,Yuncheng city,were analyzed by combining geostatistics and Kriging interpolation methods.The results showed that the spatial variation of SOM and TN in the irrigation area is mainly influenced by structural factor.The spatial variations of AN,AP and AK are influenced by both structural and random factors.AP shows a patchy distribution pattern with local enrichment or deficiency.SOM content is relatively higher in the flat area in the southwest of the irrigation area and the alluvial area in the middle and lower reaches of the central irrigation area,and soil TN and AN have the similar distribution pattern.Soil AP and AK nutrient levels are higher,soil AN nutrient level is in medium,and soil SOM and TN nutrient levels are lower in the irrigation area.The cross-validation shows that ordinary Kriging interpolation could predict the spatial variation of soil nutrients in the irrigation area accurately,and its correlation coefficient is higher and stable.The suggestions are provided for precise fertilization in the irrigation area.
作者 姚瑶 罗朋 李京玲 薛恬鑫 王洪浩 YAO Yao;LUO Peng;LI Jingling;XUE Tianxin;WANG Honghao(College of Water Resources Science and Engineering,Taiyuan University of Technology,Taiyuan 030024,China)
出处 《干旱区资源与环境》 CSCD 北大核心 2023年第2期134-141,共8页 Journal of Arid Land Resources and Environment
基金 山西省水利科学技术研究与推广项目(2021LS014) 国家自然科学基金面上项目(51979289)资助。
关键词 土壤养分 半方差函数 空间变异 引黄灌区 夹马口 soil nutrients semi-covariance function spatial variation Jiamakou Yellow River irrigation area
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