In this paper, GNSS interferometric reflectometry (GNSS-IR) is firstly proposed to estimate ground surface subsidence caused by underground coal mining. Ground subsidence on the main direction of a coal seam is described by using the probability integral model (PIM) with unknown parameters. Based on the laws of reflection in geometric optics, model of GNSS signal-to-noise (SNR) observation for the tilt surface, which results from differential subsidence of ground points, is derived. Semi-cycle SNR observations fitting method is used to determine the phase of the SNR series. Phase variation of the SNR series is used to calculate reflector height of ground specular reflection point. Based on the reflector height and ground tilt angle, an iterative algorithm is proposed to determine coefficients of PIM, and thus subsidence of the ground reflection point. By using the low-cost navigational GNSS receiver and antenna, an experimental campaign was conducted to validate the proposed method. The results show that, when the maximum subsidence is 3076 mm, the maximum relative error of the proposed method-based subsidence estimation is 5.5%. This study also suggests that, based on the proposed method, the navigational GNSS instrument can be treated as a new type of sensor for continuously measuring ground subsidence deformation in a cost-effective way.

There are numerous coal mines around the Nansi Lake Provincial Nature Reserve, and the mineral resources are extremely rich. Therefore, it is necessary to effectively assess the impact of mining activities on the topsoil. Based on a focused investigation of the contamination status and ecological risks of the Nansi Lake Nature Reserve assisted by GIS, principal component analysis was combined with positive matrix factorization to quantitatively identify the sources and contributions of heavy metal(loid)s in the topsoil before conducting uncertainty analysis. The results showed that coal mining caused higher Cu, Zn, and As contamination levels, while Hg and Cd had higher eco-toxicity and biological sensitivity. Meanwhile, principal component analysis (PCA) and positive matrix factorization (PMF) modeling displayed that Hg (59.2%) was primarily generated by industrial sources (fossil fuel combustion and mercury-containing wastewater); As (70.2%), Ni (65.6%), Cr (63.5%), Pb (61.3%), Cu (60.3%), and Zn (55.8%) were generated mainly from coal mining and processing, coal fossil fuel combustion, and coal gangue dumps; Cd (79.8%) came mainly from agricultural sources. Through uncertainty analysis, the contribution of contamination sources to the heavy metal(loid)s in the topsoil, as estimated by the PMF model, was shown to be quite different. Moreover, heavy metal(loid)s with lower contributions had errors in source identification and factor quantification. This study innovatively warned management to control the hazards of heavy metal(loid)s caused by mining engineering to protect the environment of the Nansi Lake Nature Reserve and revealed the potential harmful pathways of heavy metal(loid)s.

Minesoil profiles are reconstructed by alternative soil substrates worldwide. However, some substrates lack appropriate soil characteristics and negatively affect the minesoil functions, these negative impacts are largely caused by the deterioration of macropore structure. Nevertheless, the differences of typical substrate characteristics and their influence on the deterioration are unclear. Thus, we present a case study to analyze macropore number, size, connectivity, distribution, and soil permeability of RMSs with three substrates (MSW, YRS and RM), respectively, using industrial X-ray computed tomography. The results indicated that (1) filling of substrates made adverse variations for minesoils in macropore number, Ma, ED, τ and size distribution, and the RMS filled with RM had biggest difference in macropore parameters with NCS, followed by the MSW and YRS. (2) The variations of RMSs in macropore parameters were found to be dominated by a synthetic action of substrate texture, SBD and SOM, where SOM showed significant positive correlations with most macropore parameters other than IM, and clay content and SBD showed significant negative correlations. (3) The macropore network can be linked to SP, among various macropore parameters, Ma, AM, and Ma with ED > 600 μm had significant positive correlations with it. It is suggested that the filling substrates need to be reformed from improving the substrate texture, bulk density, and organic matter content.