基于GIS和地理加权回归的砂田土壤阳离子交换量空间预测
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宁夏大学资源环境学院

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S151.9;S153.6

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国家自然科学基金项目(41867003,41461104,41761049)和宁夏高等学校科研项目(NGY2017015)资助。


Interpolation of Soil CEC of Sandy Fields Using GIS and Geographically Weighted Regression-Kriging
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College of Resources and Environmental Science,Ningxia University

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    摘要:

    土壤阳离子交换量(CEC)反映土壤保水保肥能力,研究CEC空间分布可为土壤改良和田间施肥提供理论依据。本文以宁夏香山地区砂田淡灰钙土为研究对象,在土壤CEC和理化性质相关分析基础上以普通克里格(OK)为对照,探索回归克里格(RK)和地理加权回归克里格(GWRK)在CEC空间插值上的应用,并对三者的插值精度及制图效果进行评价。描述统计表明研究区土壤CEC含量均值为10.145 cmol/kg,CEC与有机质含量呈显著正相关,与砂粒含量呈显著负相关;地统计分析表明CEC实测值、OLS残差和GWR残差块金系数分别为8.50%、6.36% 和7.02%,比值均小于25%,具有强烈空间自相关;对验证点进行插值精度分析,RK和GWRK的相对模型改进值(RI)分别为40.49%、41.50%,插值精度GWRK>RK>OK;从成图效果看,GWRK中辅助变量参与了局部回归,成图效果更加精细,揭示了更多空间变化细节。本研究结论可为土壤CEC空间预测研究提供可靠的方法借鉴。

    Abstract:

    Soil cation exchange capacity (CEC) reflects the preservation capacity of water and fertilizer of soil. Studying CEC spatial variability can provide a theoretical basis for soil improvement and field fertilization. In this study, field sampling and indoor analysis were conducted in light sierozem in Xiangshan area of Ningxia. Based on correlation analysis between CEC and physiochemical properties of soil, geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of CEC compared with ordinary Kriging (OK, as CK). Descriptive statistics showed that soil CEC averaged at 10.15 cmol/kg, and it was significantly positively correlated with SOM whilst significantly negatively correlated with sand content. Geostatistics showed that both CEC and its residuals (including OLS residual and GWR residual) had strong spatial autocorrelation (nugget value was less than 25%). Interpolation accuracies by different methods were estimated based on a data set of validation samples, and the results showed that interpolation accuracies of RK and GWRK were higher than that of OK. In addition, GWRK significantly improved the accuracy of OK interpolation of CEC due to their incorporation of auxiliary variables. The map interpolated using GWRK revealed more details of CEC distribution. The results of this study can provide useful method reference for the interpolation of soil CEC.

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王幼奇,张 兴,赵云鹏,包维斌,白一茹.基于GIS和地理加权回归的砂田土壤阳离子交换量空间预测[J].土壤,2020,52(2):421-426. WANG Youqi, ZHANG Xing, ZHAO yunpeng, BAO Weibin, BAI Yiru. Interpolation of Soil CEC of Sandy Fields Using GIS and Geographically Weighted Regression-Kriging[J]. Soils,2020,52(2):421-426

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历史
  • 收稿日期:2018-06-13
  • 最后修改日期:2018-09-03
  • 录用日期:2018-09-18
  • 在线发布日期: 2020-04-24
  • 出版日期: 2020-04-25