基于电磁感应技术的塔里木盆地北缘绿洲土壤盐分空间变异特性

 土壤盐渍化是影响绿洲农业生产、抑制作物生长的主要生态环境问题。当前，将电磁感应技术与地面实测技术相结合是监测土壤盐渍化分布及其变化的先进方法。本文以新疆渭干河-库车河三角洲绿洲为研究区，以电磁感应仪在水平模式下（EM_H）和垂直模式下（EM_V）所获取的土壤表观电导率数据以及野外实测数据为基础，通过建立EM_V和EM_H与土壤盐分含量及组成元素的多元线性回归模型，采用泛克里格法（Universal Kriging）对研究区两个关键季节（干季、湿季）的土壤盐分含量及组成的空间变异特征进行了分析。结果表明：研究区干季和湿季表层盐渍土含盐量均与EM_V和EM_H具有良好的相关性，以EM_V+EM_H为自变量建立的土壤盐分解译模型的精度较高，且通过0.01水平检验；研究区干、湿两季的表层土壤含盐量数据符合P-P正态分布，空间分布均呈现强相关性；采用能够充分考虑到干旱区表层土壤盐分空间变异的球状套合模型，能够更好地拟合土壤表层含盐量的空间结构；研究采用泛克里格法将解译出的土壤盐分及其主要组成离子（Na⁺、Cl^-）含量进行空间插值分析，其变化趋势与土壤含盐量的变化趋势基本一致，因而采用电磁感应技术可以有效地监测不同季节干旱区绿洲土壤盐分及其组成的空间变化。

Monitoring the Spatial Variability of Soil Salinity and Composite in Dry and Wet Seasons in North Tarim Basin monitored with Electromagnetic Induction Instruments

Soil salinization is one of the eco-environmental geological problems, which affect the oasis agricultural production and inhibit crop growth. Integrated near sensing technology based on electromagnetic induction instruments and ground sampling techniques is an advanced method for monitoring and forecasting soil salinization. In this contribution, electromagnetic induction EM38 and the soil conductivity data in horizontal mode (EM_H) and vertical mode (EM_V) and field observation data are used to evaluate soil salinity at the delta oasis between the Weigan River and the Kuqa River in the north rim of the Tarim Basin. Spatio-temporal variation of soil salinity and composite in response to dry and wet seasons is analyzed by using Universal Kriging. Our results show that EM_V is significantly correlated with EM_H in study area in wet and dry seasons, and the best multiple regression model was EM_V+EM_H as independent variable in the three models, all achieved 1% significance level. The top layer soil salt content data, which used EM38 to interpreted in accordance with P-P normal distribution in study area in dry and wet seasons, and shows strong spatial autocorrelation. Considering the scale dependency of spatial variation, the nested spherical models are fitted for semi-variance of top soil. Spatio-temporal distribution maps of soil salinity and its main component ions, include Na⁺ and Cl^- for top soil layers were also mapped. And the trend is consistent. So we can monitor spatial variability of soil salinity and its composition in dry and wet seasons using electromagnetic induction instruments.