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基于GIS和地统计学的土壤养分的空间异质性研究:以红河县迤萨镇为例
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  • 分类:P[天文地球]
  • 作者机构:[1]中国科学院地理科学与资源研究所,北京100101, [2]中国科学院大学,北京100049
  • 相关基金:National Natural Science Fund of China (31200376).
中文摘要:

云南红河哈尼稻作梯田系统是全球重要农业文化遗产保护试点之一。土壤养分是土壤肥力的重要标志,对遗产地土地的可持续利用具有重要作用。运用GIS和地统计学相结合的方法,对红河县迤萨镇的土壤pH、有机质、全氮、碱解氮、有效磷、速效钾的空间变异及分布特征进行了分析。研究结果表明,该区域内的土壤pH、有机质、全氮、碱解氮、速效钾显示出中等变异,其变异系数分别为12.54%、40.14%、40.00%、34.89%、50.48%;有效磷显示出强变异,其变异系数为102.13%;土壤pH、有机质、全氮和速效钾的理论模型为指数模型,有效磷的理论模型为球状模型;土壤全氮、有效磷和速效钾的空间分布状况主要受结构性因子的影响,pH、有机质和碱解氮的空间分布状况受结构性因子和随机因子的共同影响;Kriging插值图较为直观地描述了迤萨镇土壤养分的空间分布状况。通过对土壤各种养分的空间分布状况,对于及时调整施肥等农业管理措施具有一定的指导作用,是进行精准施肥研究的基础工作。

英文摘要:

Hani rice terraces system is one of the Globaly Important Agricultural Heritage Systems (GIAHS) pilot sites selected by FAO. Soil nutrients are an important symbol of soil fertility, and play an important role in the sustainable utilization of land. Based on geo-statistics and GIS, the spatial variation of pH, organic matter, total nitrogen, alkaline hydrolyzable nitrogen, available phosphorus and available potassium in the soil in Yisa (a town in Honghe County, Yunnan Province) was studied. The results show that the spatial variability of pH, organic matter, total nitrogen, alkaline hydrolyzable nitrogen and available potassium exhibited medium spatial variability, and the coefficients of variation are 12.54%, 40.14%, 40.00%, 34.89%, and 40.00% respectively. Available phosphorus exhibited strong spatial variability, and the coefifcient of variation is 102.13%. The spatial variation of pH, organic matter, total nitrogen, alkaline hydrolyzable nitrogen and available potassium fit the index mode, however, the spatial variation of available phosphorus ifts the spherical model. Total nitrogen, available phosphorus and available potassium were greatly affected by soil structural factors, while pH, organic matter and alkaline hydrolyzable nitrogen were affected by both structural and random factors. The spatial distribution of soil nutrients in Yisa was intuitively characterized by Kriging interpolation. It is very important to understand the spatial distribution of soil nutrients, which wil provide the guidance for adjusting agricultural management measures such as fertilization.

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