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首页> 外文期刊>Geoderma: An International Journal of Soil Science >Digital mapping of A-horizon thickness using the correlation between various soil properties and soil apparent electrical resistivity
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Digital mapping of A-horizon thickness using the correlation between various soil properties and soil apparent electrical resistivity

机译:利用各种土壤特性与表观电阻率之间的相关性对水平视线厚度进行数字绘图

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摘要

Conventional soil science methods for the estimation of the spatial variations of soil properties within landscapes are destructive, time consuming, and do not allow the estimation of the short range variability. Recent advances in geomatic global positioning systems and sensors offer new possibilities for the mapping of spatially varying soil patterns. Although geophysical techniques offer an alternative to traditional soil sampling methods, the resulting data are still often misinterpreted, especially in terms of the interrelationships between, for example, soil apparent electrical resistivity (rho) and several soil physical or chemical properties. Our main objective was to test the suitability of using p measurements for mapping the thickness of the organo-mineral A-horizon (ThickA). rho was mapped (0-0.5 m), using an RM15, in a highly water eroded field plot of 300 m(2) showing large variations in ThickA, but no significant variations in soil clay and nutrient content. The correlations between p and ThickA, the top-soil water content (theta(0.1)), and the bulk density (BD0.1) were determined at the nodes of a regular grid of 2 m (n = 96). Principal Component Analysis (PCA) was used to identify the impact of the different soil properties on the p data. ThickA varied between 0.17 and 0.3 m, and p between 1046 and 3864 Omega m. There was a significant correlation between rho and ThickA (r = 0.56) and also between theta(0.1) (r = 0.23) and BD0.1 (r = 0.22). If it was assumed that theta(0.1) and BD0.1 were constant over the study plot then there was a correlation between rho and ThickA with an r of 0.88, thus making possible the accurate mapping of ThickA (MAE = 0.017 m; i.e., 7% of the average value of ThickA). Prediction (MAE = 0.015 m) was only slightly improved through the use of regression kriging of ThickA with rho recalculated as the covariate.This result showed that apparent soil electrical resistivity measurements could be very successful for estimating A-horizon thickness provided that limited information on top-soil characteristics is included in the mapping process
机译:用于估算景观内土壤特性空间变化的常规土壤科学方法具有破坏性,耗时且不允许估算短程变化性。地理全球定位系统和传感器的最新进展为绘制空间变化的土壤模式提供了新的可能性。尽管地球物理技术提供了传统土壤采样方法的替代方法,但是所得数据仍然经常被误解,特别是在例如土壤表观电阻率(rho)与几种土壤物理或化学特性之间的相互关系方面。我们的主要目标是测试使用p测量来绘制有机矿物质A地平线(ThickA)厚度的适用性。在300 m(2)高度水蚀的田间图中,使用RM15将rho映射(0-0.5 m),显示ThickA的变化很大,但土壤黏土和养分含量没有明显变化。在2 m(n = 96)的规则网格的节点处确定p与ThickA,表层土壤水含量(theta(0.1))和堆积密度(BD0.1)之间的相关性。主成分分析(PCA)用于确定不同土壤性质对p数据的影响。厚度A在0.17和0.3 m之间变化,p在1046和3864Ωω之间变化。在rho和ThickA之间(r = 0.56),以及theta(0.1)(r = 0.23)和BD0.1(r = 0.22)之间存在显着相关性。如果假设theta(0.1)和BD0.1在研究图中恒定,则rho和ThickA之间存在相关性,r为0.88,因此可以精确地绘制ThickA(MAE = 0.017 m;即,平均值的7%。预测(MAE = 0.015 m)仅通过使用ThinA的回归克里格法和重新计算的rho作为协变量而略有改善。结果表明,在有限的信息下,表观土壤电阻率测量可以非常成功地估计水平视线的厚度映射过程中包括表层土壤特征

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