基于电磁感应技术的土壤剖面盐分空间分布建模研究
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新疆大学资源与环境科学学院,新疆大学资源与环境科学学院,新疆大学资源与环境科学学院,新疆大学资源与环境科学学院

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新疆维吾尔自治区青年科技创新人才培养工程(2013711014);国家自然科学基金项目(U1303381,41261090,41130531,41161063);教育部新世纪优秀人才支持计划(NCET-12-1075);霍英东青年教师基金项目(121018);教育部长江学者计划创新团队计划(IRT1180);新疆维吾尔自治区研究生科研创新项目(XJGRI2013023)


Modeling of the spatial distribution of soil profile salinity based on the electromagnetic induction technique
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College of Resources and Environment Sciences,Xinjiang University,,

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    摘要:

    土壤盐渍化问题是干旱半干旱地区农业发展的主要障碍,也是制约荒漠植物生长状况的关键因素之一,严重影响到绿洲生态环境的稳定与安全。研究土壤剖面盐分的分布情况,能及时探究盐渍化对生态的影响。以渭干河-库车河三角洲绿洲为研究靶区,利用电磁感应仪技术与传统采样方法获取该地区典型地块的土壤电导率,剖析其剖面分布特征,在建立磁感式表观电导率和土壤样本实测电导率之间的线性混合模型的基础上,采用自然邻近插值方法解析和评估研究区土壤剖面盐分的空间分布特征。结果表明:研究区土壤电导率具有较强的表聚性与空间变异强度,土壤主体属于中度盐渍化类型;基于各深度层土壤电导率与磁感表观电导率所构建的3种线性混合模型均能达到0.01的显著性水平,其中磁感表观电导率两种模式相结合解译模型预测精度最高;自然邻近法插值结果直观反映研究区土壤剖面盐分的空间分布状况,与水平模式和垂直模式相结合的土壤盐分解译模型相结合则能够更有效的提高土壤盐分空间分布的预测精度。研究结果表明,借助构建的土壤盐分解译模型可对研究区土壤盐渍化空间分布情况进行快速监测与评估,为该区土壤盐渍化的防治提供了一定的技术支撑。

    Abstract:

    Soil salinization is the main obstacle to agricultural development in arid and semi-arid regions. It is also one of the key limitations on the growth of eremophytes, which seriously affect the stability and safety of the ecological environment in oases. Oases are unique among desert ecosystems because of the availability of generally sufficient water resources that can sustain a wider range of human activities. Over time, oases often become highly developed locales in arid and semi-arid regions, with concentrated human populations and activities. With the development of oasis irrigation agriculture, soil salinization and soil secondary salinization caused by irrigation has gradually become the largest obstacle for sustainable oasis agricultural development. Study of the distribution of soil salt content in soil profiles can determine the influence of salinization on oasis ecology and environment. In this study, using the Weigan-Kuqa Delta Oasis as the research area, the soil electrical conductivities of typical plots in the region were obtained using an electromagnetic induction technique and a traditional soil sampling method. A linear mixed model between magnetic inductive apparent conductivity and the observed conductivities of the soil samples indicates that the apparent electricity conductivity is a good surrogate for soil salinity. We therefore used the apparent soil electricity conductivity to examine the spatial distribution of soil salt content at different depths in the soil profile because obtaining such data is often much more cost-effective. We employed a natural neighbor interpolation approach at various depths to analyze and evaluate the spatial distribution features of the soil profile salinity. The results showed that the soil in the research area has strong surface aggregation and spatial variation, and that the soil body is moderately salinized. Soil salinization is clearly higher in the desert areas and interlaced border areas than within the oasis. Soil salt content showed a decreasing trend from the desert areas and interlaced border areas to the internal oasis. The three linear mixed models, built based on soil electrical conductivities and magnetic inductive apparent conductivities of the soils at each depth, all reached the 0.01 significance level. Both the vertical and horizontal apparent electrical conductivities were significantly related to the spatial distribution of soil salt content in soil profiles. Further exploration indicates that the horizontal apparent electrical conductivity best measures the surface soil salinization, while the vertical apparent electricity conductivity best measures the deep soil salt content. Additionally, combining both the horizontal and vertical apparent electricity conductivities produces more efficient interpretation of soil salinization and better spatial interpolation results than either method alone. The result of the natural neighbor interpolation visually reflects the spatial distribution status of the soil profile salinity in the research area. The interpretation models of soil salinity obtained by combining horizontal and vertical modes can effectively increase the prediction accuracy of the spatial distribution of soil profile salinity. Through intensive field work and soil sampling practices, coupled with a local spatial interpolation approach (the natural neighbors), this study investigates the feasibility of applying electromagnetic induction devices to evaluating, monitoring, and predicting soil salinization at various soil depths in the Werigan-Kuqa Delta Oasis. Our results show that the spatial distribution of soil salinization significantly contributes to efficient local soil salinization management and possible treatment, and thus can provide technical support for preventing and controlling soil salinization in this region.

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邓凯,丁建丽,杨爱霞,王瑾杰.基于电磁感应技术的土壤剖面盐分空间分布建模研究.生态学报,2016,36(20):6387~6396

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