A non-destructive detection of soil bulk density in reclaimed land of opencast coal mines using ground penetrating radar method

IF 6.8 1区 农林科学 Q1 SOIL SCIENCE
Tiantian Ye , Jingpeng Wang , Xiangyu Min , Jinman Wang
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引用次数: 0

Abstract

Land reclamation of opencast coal mines is of critical for environmental restoration and sustainable land use. Soil bulk density (SBD) is an important index to evaluate the impact of land reclamation on soil quality in mining areas. However, the traditional soil sampling method is destructive and time-consuming. Therefore, developing a non-destructive, repeatable, high-precision, and efficient method for detecting the SBD of reclaimed soil in opencast mining areas is required. This study evaluated the feasibility of using ground penetrating radar (GPR) to estimate SBD in reclaimed mining areas. The south dump of the Antaibao opencast coal mine in Pinglu District of Shuozhou City, Shanxi Province, China, was selected for the study. The random Hough transform algorithm was used to identify automatically the hyperbolic reflection in radar images and obtain the soil characteristic information from different locations. Inverse distance weighted interpolation was used to identify and characterize SBD and the soil dielectric constant (SDC) in 3 different soil layers and 2 measuring points. The method provided the SDC with high precision. The Pearson correlation coefficient (r) between the estimated and measured SDC was the highest at sampling point S1 (0.935), and the root mean square error (RMSE) was the lowest (0.272, from 0.272 to 0.542), indicating the feasibility of using the SDC to characterize SBD. The r for SBD and SDC ranged from 0.689 to 0.857 at sampling point S1, and from 0.724 to 0.747 at sampling point S2. The estimated and measured SBD had different distributions at different soil depths. A numerical model describing the relationship between SBD and SDC was used for the non-destructive identification of SBD with high precision. The proposed method expands the application potential of GPR to detect soil properties and provides a theoretical basis and technical support for the non-destructive detection of soil physical properties using GPR. This study contributes advancing non-destructive soil assessment techniques and provides a practical tool for assessing and optimizing reclaimed soil properties in opencast coal mine rehabilitation projects.
利用探地雷达法无损检测露天煤矿复垦土地土壤容重
露天煤矿土地复垦是环境恢复和土地可持续利用的关键。土壤容重(SBD)是评价矿区土地复垦对土壤质量影响的重要指标。然而,传统的土壤取样方法破坏性大,耗时长。因此,开发一种无损、可重复、高精度、高效的露天矿复垦土壤SBD检测方法势在必行。本文对利用探地雷达估算复垦矿区SBD的可行性进行了评价。选取山西省朔州市平陆区安太堡露天煤矿南排土场为研究对象。采用随机霍夫变换算法自动识别雷达图像中的双曲反射,获取不同位置的土壤特征信息。采用逆距离加权插值法对3个不同土层和2个测点的SBD和土壤介电常数(SDC)进行了识别和表征。该方法具有较高的SDC精度。在抽样点S1处,SDC估计值与实测值之间的Pearson相关系数(r)最高(0.935),均方根误差(RMSE)最低(0.272,范围为0.272 ~ 0.542),表明用SDC表征SBD是可行的。SBD和SDC在S1采样点的r值为0.689 ~ 0.857,在S2采样点的r值为0.724 ~ 0.747。在不同的土壤深度,SBD的估计值和实测值具有不同的分布。利用描述SBD与SDC关系的数值模型,实现了SBD的高精度无损识别。该方法拓展了探地雷达探测土壤性质的应用潜力,为探地雷达无损探测土壤物理性质提供了理论基础和技术支持。该研究有助于推进非破坏性土壤评价技术,为露天煤矿复垦工程复垦土壤性质评价与优化提供实用工具。
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来源期刊
Soil & Tillage Research
Soil & Tillage Research 农林科学-土壤科学
CiteScore
13.00
自引率
6.20%
发文量
266
审稿时长
5 months
期刊介绍: Soil & Tillage Research examines the physical, chemical and biological changes in the soil caused by tillage and field traffic. Manuscripts will be considered on aspects of soil science, physics, technology, mechanization and applied engineering for a sustainable balance among productivity, environmental quality and profitability. The following are examples of suitable topics within the scope of the journal of Soil and Tillage Research: The agricultural and biosystems engineering associated with tillage (including no-tillage, reduced-tillage and direct drilling), irrigation and drainage, crops and crop rotations, fertilization, rehabilitation of mine spoils and processes used to modify soils. Soil change effects on establishment and yield of crops, growth of plants and roots, structure and erosion of soil, cycling of carbon and nutrients, greenhouse gas emissions, leaching, runoff and other processes that affect environmental quality. Characterization or modeling of tillage and field traffic responses, soil, climate, or topographic effects, soil deformation processes, tillage tools, traction devices, energy requirements, economics, surface and subsurface water quality effects, tillage effects on weed, pest and disease control, and their interactions.
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