Quan Li
Shijie Song
Haizhen Ma1- 1Power China Northwest Engineering Corporation Limited, Xi’an, China
- 2College of Geology and Environment, Xi ‘an University of Science and Technology, Xi’an, China
- 3School of Architecture and Civil Engineering, Liaocheng University, Liaocheng, China
Background: A scientific understanding of soil erosion in coal mining subsidence areas is crucial for promoting green development and ecological restoration within the large coal bases of the Yellow River’s middle reaches.
Methods: This study focused on the shallow soil layer (0–40 cm) of a loess mining subsidence area and typical slopes in northern Shaanxi. Integrating field sampling, laboratory measurements, and model-based calculations, we analyzed the impact of mining subsidence on soil anti-erodibility by examining the coupled “slope position × soil depth” effect.
Results: The results indicate that: (1) Mining subsidence significantly reduced the content of water-stable aggregates (>0.25 mm) and decreased the mean weight diameter of soil aggregates on the loess slope, with the >0.25 mm aggregate content being the most affected; (2) The adverse effect of subsidence on key soil anti-erodibility indicators weakened progressively from the slope top to the slope toe. The 0–20 cm soil layer at the slope top showed the greatest sensitivity; (3) Following subsidence, the comprehensive soil anti-erodibility index decreased significantly, indicating markedly enhanced erosion susceptibility. The most pronounced reduction (97.13%) was observed in the “slope top + 0–20 cm soil layer”.
Conclusion: The “slope top + 0–20 cm soil layer” should be prioritized as a key area for erosion control on subsided loess slopes. These findings provide a scientific basis for targeted soil erosion management in coal mining subsidence areas of northern Shaanxi.
1 Introduction
China’s ‘Dual Carbon Goals’ strategy has accelerated the transition of coal from a dominant to a foundational and underpinning role in the national energy structure, while simultaneously reinforcing its critical function in ensuring national energy security (Wang et al., 2025; Wang et al., 2023). The middle reaches of the Yellow River Basin, which host six national-level coal production bases—Northern Shaanxi, Huanglong, Shendong, Jinzhong, Jindong, and Jinbei—constitute a critical coal-producing region in China, accounting for over 40% of the nation’s total coal production (Peng and Bi, 2020; Shen et al., 2022). However, the large-scale underground mining activities required to support this output have induced widespread land subsidence, thereby posing a significant threat to the ecological security of the middle Yellow River region. A particularly severe manifestation of this threat is the intensification of regional soil and water loss (Song et al., 2025; Song et al., 2022), which stands in direct conflict with the explicit directive to “focus on soil and water conservation” enshrined in the Yellow River Basin Ecological Protection and High-Quality Development Plan. A prominent illustration of this conflict can be found in the Northern Shaanxi Mining Area, where coal subsidence areas exhibit a soil erosion modulus ranging from 4,000 to 5,000 t/(km2·a), a value 4 to 5 times greater than the regional soil and water conservation target (Song et al., 2024). This acute contradiction between coal extraction activities and soil-water conservation objectives renders the comprehensive management of mining subsidence areas an urgent priority for achieving the overarching goals of ecological protection and high-quality development in the Yellow River Basin (Li et al., 2019b). Consequently, a scientific understanding and precise control of the soil erosion effects induced by mining subsidence are of strategic importance for facilitating ecological restoration in the Northern Shaanxi mining areas and for advancing the broader agenda of ecological protection and high-quality development in the middle reaches of the Yellow River.
In recent years, soil erosion triggered by coal mining subsidence has gained growing attention as a critical issue in the study of ecological degradation and restoration in mining areas worldwide. Research conducted across various spatial scales has consistently demonstrated the aggravation of soil erosion in affected regions. At the macro scale, studies employing integrated modeling and geospatial techniques have revealed pronounced erosion patterns. For instance, Karan et al. (2019) combined the RUSLE model with the Analytic Hierarchy Process (AHP) to identify severe soil loss zones exceeding 950 km2 in India’s Damodar River Basin. Mhaske et al. used a GIS-integrated RUSLE model to estimate the spatial distribution of average annual soil and water loss in the Saranda region and calculated the soil erosion modulus (Mhaske et al., 2021). Similarly, Li et al. (2024) monitored increasing soil erosion rates in the Binchang mining area (2014–2019) using remote sensing and the RUSLE model. Liu et al. (2022) integrated a geographical detector with the USLE model and documented a significant rise in soil erosion in the Shendong mining area from 1989 to 2019. Wang et al. (2011) applied GIS and RS techniques to show that the Huainan mining area evolved into a high-intensity erosion zone after 2000. Further supporting these findings, Song et al. (2025) used the RUSLE model to confirm a substantial increase in soil erosion volume following subsidence in the Northern Shaanxi mining area.
At micro and meso scales, mechanistic insights into soil property alteration and erosion processes have been uncovered. Soni et al. (2014) conducted field surveys that established a clear link between mining subsidence and both soil quality degradation and heightened erosion intensity in India’s Kamptee coal mine. Howladar (Howladar, 2022) attributed the worsened soil and water loss observed in Bangladesh’s Barapukuria coal mine to a significant reduction in soil infiltration capacity induced by subsidence. Ma et al. analyzed the multi-hazard effects of surface induced by underground coal mining using high-precision remote sensing techniques. (Ma et al., 2023); Chen et al. (2015) investigated the spatiotemporal variations in topsoil clay content within the coal mining subsidence area of Huaibei’s Shajiang black soil region and further analyzed the dynamics of slope soil detachment rates through simulated rainfall experiments. Using 137Cs tracer technology, Zhang et al. (2015) revealed intensified soil erosion across entire subsidence slopes in the Jiaozuo mining area. Additionally, Yang and Lei. (2021) explored the influence of underground mining intensity on surface topographic factors in the Shendong mining subsidence area, thereby providing valuable context for understanding the geomorphological drivers of erosion.
The macroscopic characteristics of soil erosion in coal mining subsidence areas are essentially a comprehensive manifestation of the spatiotemporal integration and superposition of soil erosion effects generated by micro-topographies (slopes) of “varying shapes and sizes” within the area. Therefore, accurately understanding the potential capacity and processes of soil erosion on slopes in coal mining subsidence areas serves as a critical foundation for achieving precise prevention and control of soil and water loss in these regions. Within the field of soil and water conservation research, soil anti-erodibility is widely recognized as a comprehensive indicator that reflects the soil’s inherent capacity to resist detachment and transport by external erosive forces such as wind and water (Nciizah and Wakindik, 2014). This parameter is often used in conjunction with the concept of soil erodibility to holistically reflect the susceptibility of soil to erosion. Soil anti-erodibility and soil erodibility are an organic whole of unity of opposites (Zhang et al., 2023). Previous research on soil anti-erodibility has primarily concentrated on investigating its influencing factors (Amezketa et al., 1996; Woodburn and Kozachyn, 1956; Stavi and Yizhaq, 2020) and developing methods for its quantitative characterization (Sillero-Medina et al., 2020) across different regional contexts. However, targeted studies conducted specifically within the unique and disturbed environment of coal mining subsidence areas remain extremely scarce (Song et al., 2024). In light of this identified research gap, the present study focuses specifically on the subsidence slopes located in the loess mining area of Northern Shaanxi within the middle reaches of the Yellow River. Through a methodology combining field sampling, laboratory measurements, and model calculations, this research aims to systematically reveal the variation patterns of soil anti-erodibility under the coupled influence of ‘slope position and soil depth’. The findings derived from this investigation are expected to provide a scientific basis for the in-depth understanding and precise control of soil erosion effects in coal mining subsidence areas.
2 Study area overview
The Ningtiaota Coal Mine in the Northern Shaanxi Mining Area was selected as the study area (Figure 1). The terrain is generally higher in the northwest and southwest, and lower in the central part (Bi et al., 2022). The landforms are predominantly loess gully and sandy grassland types. The mining area is located in a mid-temperate semi-arid continental climate zone, characterized by variable temperatures, long sunshine hours, high evaporation, and low rainfall, with an average annual precipitation of only about 400 mm. Surface soils in the area are primarily comprised of aeolian sandy soil, chestnut soil, and loessal soil, and the vegetation is mainly dominated by Artemisia desertorum, Salix psammophila, and Caragana korshinskii. The primary type of soil erosion in the region is water erosion, with a multi-year average soil erosion modulus of approximately 5,000 t/(km2·a) (Li et al., 2014).
Figure 1. Location diagram of the study area: (a) Location map of the study area; (b) Morphology of the loess slope; (c) Loess gully landform; (d) The actual situation of soil erosion.
The mine primarily extracts the No. 2-2 coal seam, with an average burial depth of about 250 m and an average thickness of about 6.0 m. The No. 2-2 coal seam is mined using the longwall fully mechanized mining method, with a typical mining height of around 5 m. The roof is managed using the total caving method, resulting in significant surface subsidence and deformation, with an average subsidence factor of about 0.7 (Song et al., 2022).
3 Materials and methods
3.1 Sample collection
The sampling targeted the most abundant and widely distributed type of loess slope within the coal mining subsidence area of the Ningtiaota Coal Mine in the Northern Shaanxi mining area—a straight slope with a gradient of approximately 22°, a slope length of about 50 m, and vegetation coverage of around 43%, dominated mainly by Stipa bungeana grassland. The slope aspect aligned with the advancing direction of the underground working face. The central coordinates of the sampling area are E110°14′14.08″, N39°05′7.52″.
The sampling procedure was conducted as follows:
• Five typical subsided loess slopes were randomly selected from the central part of the subsidence area as sampling targets. Each slope was divided into three positions: the upper 10 m was designated as the slope top, the middle 30 m as the slope middle, and the lower 10 m as the slope toe.
• Sampling quadrats were randomly established at the slope top, slope middle, and slope toe of each selected subsided slope, as illustrated in Figure 2.
• Soil samples from the 0–20 cm and 20–40 cm layers within each quadrat were collected using the five-point sampling method. Two undisturbed soil samples were taken per layer using aluminum boxes (10 cm in diameter, 8 cm in height): one for determining water-stable aggregates and the other for analyzing soil mechanical composition and organic matter content. All samples were sealed and labeled (Liu et al., 2024).
• For comparison, three natural loess slopes with similar gradient, length, shape, and aspect were selected in an unmined area located 500 m northwest of the sampling zone. Soil samples were collected from these control slopes following the same sampling method and procedure.
• A total of 480 soil samples were collected and transported to the laboratory for subsequent analysis.
Figure 2. Schematic of sampling point layout.
3.2 Anti-erodibility indicators and analytical methods
Based on previous research findings from our team [26, 29], five key indicators were selected to evaluate soil anti-erodibility for loess subsidence slopes in Northern Shaanxi (Table 1, with the parameter descriptions in the table consistent with Equation 1):
• Content of soil aggregates >0.25 mm,
• Mean weight diameter (MWD) of soil aggregates,
• Content of soil fine clay particles <0.001 mm,
• Soil aggregate degree,
• Soil organic matter (SOM) content.
Table 1. Key indicators of soil erosion resistance on the loess collapse slope in Northern Shaanxi.
3.3 The corresponding analytical methods for each indicator were as follows
• The content of aggregates >0.25 mm and MWD were determined using the wet-sieving method with an XY-100 soil aggregate analyzer.
• The content of fine clay particles <0.001 mm was measured using laser diffraction with a Mastersizer 2000 (MS2000) laser particle size analyzer.
• The soil aggregate degree was determined using the pipette method with a soil particle analysis pipette apparatus.
• SOM content was measured using the potassium dichromate volumetric method (Walkley-Black method) and titrated with a German BRAND Titrette digital titrator.
All measurements for each soil sample were performed in triplicate.
3.4 Data processing and analysis methods
The collected data were organized using Microsoft Excel. Significance analysis was conducted with SPSS 24.0 software. Figures were generated using Origin 2021 and ArcGIS 10.2.
The comprehensive soil anti-erodibility index was calculated using a model specifically developed by our research team for assessing soil anti-erodibility in loess coal mining subsidence areas of the Northern Shaanxi mining region [26, 29], as presented in Equation 1.
In the Equation 1, YK represents the comprehensive soil anti-erodibility index.
Three important points require clarification:
The model was constructed using the principle of multiple linear regression, based on the comprehensive screening of key indicators for soil erosion resistance in coal mining subsidence areas through the integration of the Analytic Hierarchy Process (AHP), sensitivity analysis, and factor analysis.
The model demonstrates a high goodness-of-fit, with an R2 of 0.960. The F-test result was statistically significant (P < 0.05).
To accurately reflect the meaning of positive and negative calculated values and enhance interpretability, a standardization procedure was applied: if any calculated YK value was negative, the absolute value of the most negative YK (
4 Results and analysis
The measurement results of the key soil anti-erodibility indicators and the calculated values of the comprehensive soil anti-erodibility index for soil samples collected from different slope positions (slope top, middle slope, slope toe) at vertical depths of 0–20 cm and 20–40 cm are presented in Table 2 and Figure 3.
Table 2. Key indicators test results and comprehensive index calculation results for soil erosion resistance on subsidence slopes in the loess mining areas of Northern Shaanxi.
Figure 3. Changes in key indicators and the comprehensive index of shallow soil erosion resistance at different positions on the loess collapse slope. (a) Content of water-stable aggregates >0.25 mm at 0-20 cm depth; (b) Content of water-stable aggregates >0.25 mm at 20-40 cm depth; (c) Mean weight diameter of soil aggregates at 0-20 cm depth; (d) Mean weight diameter of soil aggregates at 20-40 cm depth; (e) Content of fine clay particles <0.001 mm at 0-20 cm depth; (f) Content of fine clay particles <0.001 mm at 20-40 cm depth; (g) Soil aggregation degree at 0-20 cm depth; (h) Soil aggregation degree at 20-40 cm depth; (i) Soil organic matter content at 0-20 cm depth; (j) Soil organic matter content at 20-40 cm depth; (k) Soil organic matter at 0-20 cm depth; (l) Soil organic matter at 20-40 cm depth.
4.1 Impact on the X1
The content of water-stable aggregates (>0.25 mm) in soil samples from the slope top, middle slope, and slope toe at depths of 0–20 cm and 20–40 cm on the subsided loess slope was measured. Based on these results, the variation in the content of these aggregates in the shallow soil at different positions of the subsided loess slope is illustrated in Figures 3a,b.
As shown in Figure 3, slope subsidence resulted in a reduction in the content of water-stable aggregates (>0.25 mm) in the shallow soil across the entire slope. Specifically:
• In the 0–20 cm layer, the content exhibited reductions of 60.85%, 45.61%, and 27.33% at the slope top, middle slope, and slope toe, respectively, relative to the control (CK).
• In the 20–40 cm layer, reductions were 27.28%, 16.55%, and 11.88% at the slope top, middle slope, and slope toe, respectively.
All these changes were statistically significant (P < 0.05). These findings indicate two key observations: (1) The reduction effect of mining subsidence on water-stable aggregate content (>0.25 mm) was more pronounced in the 0–20 cm layer than in the 20–40 cm layer; (2) The reduction magnitude followed the order: slope top > middle slope > slope toe. The “slope top + 0–20 cm soil layer” combination exhibited the most substantial reduction and demonstrated the highest sensitivity to mining subsidence effects.
4.2 Impact on the X2
The MWD of soil aggregates from different slope positions and depths were measured, with results presented in Figures 3c,d.
In the 0–20 cm layer, MWD exhibited reductions of 55.68%, 44.94%, and 36.26% at the slope top, middle slope, and slope toe positions, respectively.
In the 20–40 cm layer, reductions were 19.44%, 14.29%, and 15.38% at the slope top, middle slope, and slope toe, respectively.
All differences were statistically significant (P < 0.05). These findings indicate two key observations: (1) The magnitude of MWD reduction induced by subsidence was greater in the 0–20 cm layer than in the 20–40 cm layer; (2) The reduction followed the order: slope top > middle slope > slope toe, with the “slope top + 0–20 cm layer” combination exhibiting the most substantial decrease and highest sensitivity to subsidence effects.
4.3 Impact on X3
The content of fine clay particles (<0.001 mm) were measured, with variations presented in Figures 3e,f.
Subsidence resulted in a decrease in fine clay particle content across the slope:
• In the 0–20 cm layer, the slope top, middle slope, and slope toe exhibited reductions of 17.45%, 11.91%, and 11.71%, respectively.
• In the 20–40 cm layer, reductions were more pronounced: 26.44%, 21.35%, and 20.49% at the slope top, middle slope, and slope toe, respectively.
All changes were statistically significant (P < 0.05). These findings indicate: (1) The reduction effect was more pronounced in the 20–40 cm layer than in the 0–20 cm layer; (2) The reduction magnitude followed the order: slope top > middle slope > slope toe, with the “slope top +20–40 cm layer” combination being most severely affected.
4.4 Impact on X4
Variations in soil aggregate degree are presented in Figures 3g,h.
Subsidence resulted in a reduction in soil aggregate degree across the slope:
In the 0–20 cm layer, the slope top, middle slope, and slope toe exhibited reductions of 22.97% (P < 0.05), 11.56% (P < 0.05), and 2.75% (statistically non-significant at the slope toe), respectively.
In the 20–40 cm layer, reductions were 19.12% (P < 0.05), 8.94%, and 2.71% at the slope top, middle slope, and slope toe, respectively.
These results indicate: (1) The reduction effect was comparable between the 0–20 cm and 20–40 cm layers; (2) The reduction extent followed the order: slope top > middle slope > slope toe, with the “slope top + 0–20 cm layer” combination demonstrating the highest sensitivity.
4.5 Impact on X5
Variations in SOM content are depicted in Figures 3i,j.
Subsidence resulted in a reduction in SOM content across the slope:
In the 0–20 cm layer, the slope top, middle slope, and slope toe exhibited reductions of 29.09%, 22.77%, and 14.66%, respectively (all P < 0.05).
In the 20–40 cm layer, the slope top, middle slope, and slope toe exhibited reductions of 27.55%, 14.11%, and 5.24%, respectively.
These results indicate: (1) The reduction was slightly greater in the 0–20 cm layer; (2) The order remained slope top > middle slope > slope toe, with the “slope top + 0–20 cm layer” combination exhibiting the most substantial loss.
4.6 Impact on YK
The comprehensive soil anti-erodibility index (YK) was calculated, with variations presented in Figures 3k,l.
Subsidence significantly reduced the comprehensive anti-erodibility index across the entire slope:
In the 0–20 cm layer, YK exhibited reductions of 97.13%, 68.32%, and 45.19% at the slope top, middle slope, and slope toe, respectively.
In the 20–40 cm layer, reductions were 91.77%, 64.83%, and 47.60% at the slope top, middle slope, and slope toe, respectively.
All changes were statistically significant (P < 0.05). This indicates that:
• The reduction in the comprehensive index was substantial and comparable across the two depth layers.
• The reduction extent consistently followed the order: slope top > middle slope > slope toe. The “slope top + 0–20 cm soil layer” was the most severely impacted, exhibiting the largest decrease in the comprehensive anti-erodibility index, confirming its status as the area most sensitive to mining subsidence.
Furthermore, as derived from Equation 1, the coefficient for the mean weight diameter of soil aggregates is the largest at 1.040, indicating its greatest contribution to the comprehensive soil erosion resistance index. This is followed by the content of fine clay particles <0.001 mm in soil. In contrast, the content of water-stable aggregates >0.25 mm in soil, soil aggregation degree, and soil organic matter content contribute relatively less to the comprehensive soil erosion resistance index.
5 Discussion
Coal mining-induced subsidence induces various types and degrees of movement and deformation at different positions of loess slopes, ultimately exerting differential effects on soil anti-erodibility via alterations in soil aggregate characteristics, soil texture, and soil organic matter content.
At the slope top of the subsided loess slope, mining subsidence induces a significant tensional effect (Song et al., 2022), resulting in shallow soil loosening and substantial increase in porosity (Zhu et al., 2020). This, on one hand, creates additional pathways for external erosive forces such as surface erosion, promoting the loss of fine clay particles (<0.001 mm) and soluble organic matter via wind and subsurface flow (Wang et al., 2017). On the other hand, the marked increase in soil porosity enlarges the soil evaporation surface area, leading to rapid decreases in soil moisture content and increases in soil solution concentration. This consequently induces a ‘flocculation-sedimentation effect’ of fine particles, further aggravating the reduction in fine clay content (Wang et al., 2021). The modified porosity at the slope top also enhances oxygen exchange between the atmosphere and soil, accelerating oxidative decomposition of soil organic matter (SOM) and directly reducing its content (Xia et al., 2010). The diminished cementing action of SOM further contributes to the decline in soil aggregate stability (Song et al., 2021).
Concurrently, mining subsidence significantly alters the soil physicochemical environment (water, nutrients, air, temperature), inducing substantial changes in soil microbial habitats and thereby reducing microbial populations (Song et al., 2021; Song et al., 2023). Extensive research has established that soil microorganisms play a critical role in the formation and stabilization of soil aggregates (Ren et al., 2022; Blankinship et al., 2016). Reduced microbial abundance not only directly results in a reduction in the content of water-stable aggregates (Zheng et al., 2014) but also leads to a decrease in the mean weight diameter (MWD) of soil aggregates owing to the reduction in large aggregates (Li et al., 2019a). Diminished microbial activity also contributes to the reduction in SOM content (Liang et al., 2019).
Furthermore, the tensional effect at the slope top induces severe soil cracking and sliding, damaging or severing plant roots. This not only impairs the root system’s functional roles in penetrating, enmeshing, and binding soil particles (Tan et al., 2025; Hao et al., 2021)—resulting in reduced soil aggregate content (Frédéric et al., 2008; Pohl et al., 2012)—but also diminishes root exudation capacity, exacerbating SOM loss. These processes collectively explain why the five key soil anti-erodibility indicators (content of >0.25 mm water-stable aggregates, MWD of soil aggregates, content of <0.001 mm fine clay particles, soil aggregate degree, and SOM content) and the comprehensive soil anti-erodibility index exhibited the most significant reductions at the slope top.
At the middle slope, mining subsidence induces a noticeable steepening effect (Song et al., 2022), thereby increasing shallow soil porosity. Through analogous mechanisms described previously, the five key anti-erodibility indicators at the middle slope decreased to varying degrees. However, the magnitude of surface deformation at the middle slope is smaller than at the slope top, resulting in lower losses of soil aggregates, fine clay particles, and SOM compared to the slope top. Additionally, fine particles and soluble organic matter from the slope top are transported downslope by surface wind and runoff, providing partial replenishment to the middle slope (Song et al., 2023). This partially alleviates the loss of soil aggregates and other components at this position. These factors collectively contribute to the observation that the decreases in the five key anti-erodibility indicators and comprehensive anti-erodibility capacity at the middle slope were less severe than at the slope top.
At the slope toe, subsidence induces a distinct compressive effect (Song et al., 2022), leading to relatively limited changes in soil porosity. Consequently, the reductions in the five key anti-erodibility indicators are relatively minor. Furthermore, the cumulative replenishment from the slope top and middle slope to the slope toe contributes to the relatively small decreases observed in the key soil anti-erodibility indicators and comprehensive anti-erodibility capacity at the slope toe (Song et al., 2023).
The movement and deformation caused by coal mining subsidence can lead to varying degrees of changes in the physical structure of soil layers at different depths on any slope. As a result, the changes in key indicators of soil erosion resistance also differ, but ultimately, these changes combine to collectively cause a decline in the comprehensive soil erosion resistance capacity. This may explain why, under the same subsidence influence, the changes in the five key indicators of soil erosion resistance in the 0–20 cm soil layer and the 20–40 cm soil layer show significant differences, yet the extent of decline in comprehensive erosion resistance capacity is relatively similar between the two layers.
The findings of this study differ from some previous research results, primarily due to differences in the topography, subsidence characteristics, and types of the study area. In mining areas with flat and uniformly undulating terrain, coal mining subsidence often forms continuous and uniform depressions or basins, which exhibit certain soil and water conservation characteristics, such as “water convergence” and “soil accumulation” (Zheng et al., 2022). However, the study area of this research is characterized by steep terrain and crisscrossed gullies. As a result, the surface deformation within the coal mining subsidence area here is discontinuous, with densely distributed and deep surface cracks (some even connected to underground goafs). This makes it difficult for the area to become a zone of water and soil accumulation from surrounding regions. Instead, it exhibits erosion features such as “water loss” and “soil loss” (Bai et al., 2020; Yang et al., 2025; Qiu et al., 2025), leading to an increase in the soil erosion modulus within the subsidence area and exacerbating soil and water loss.
Based on the above understanding, it is recommended to prioritize the slope crest area of subsidence slopes as the key zone for soil erosion prevention and control at the slope scale in coal mining subsidence areas. The 0–20 cm soil layer should be regarded as the target horizon for erosion mitigation efforts. Additionally, enhancing the stability of soil aggregates and increasing the content of fine clay particles (<0.001 mm) can serve as effective measures to control and alleviate soil erosion.
6 Conclusion
This study systematically assessed the effects of coal mining subsidence on soil anti-erodibility in loess slopes of Northern Shaanxi. The primary findings are summarized as follows:
• Coal mining subsidence causes comprehensive deterioration of five key soil erosion resistance indicators in the shallow soil layer (0–40 cm) of loess slopes: the content of water-stable aggregates >0.25 mm, the mean weight diameter of soil aggregates, the content of fine clay particles <0.001 mm, the soil aggregation degree, and the soil organic matter content. Among these, the content of water-stable aggregates >0.25 mm is the most significantly affected by coal mining subsidence, with a maximum decrease of 60.85%.
• The variation patterns of key soil erosion resistance indicators in the shallow soil layer of loess subsidence slopes exhibit distinct vertical differentiation characteristics, mainly manifested as the decreases in the content of water-stable aggregates >0.25 mm and the mean weight diameter of soil aggregates in the 0–20 cm soil layer are significantly greater than those in the 20–40 cm soil layer, with the former being 2.4–2.8 times that of the latter.
• A distinct spatial gradient of subsidence impact was observed along the slope. The degrading effect on all five key indicators diminished progressively from the slope top to the slope toe. The 0–20 cm soil layer at the slope top was identified as the most vulnerable.
• Mining subsidence led to a substantial decline in the comprehensive soil anti-erodibility index across the entire slope, indicating a significant increase in soil erosion susceptibility. The most severe degradation occurred at the “slope top + 0–20 cm soil layer” position, where the index decreased by 97.13%, thus identifying it as the critical zone for targeted erosion control in subsided loess slopes.
These findings provide a scientific foundation for designing targeted ecological restoration and soil conservation strategies in coal mining subsidence areas of the Yellow River Basin.
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Author contributions
QL: Resources, Writing – original draft, Conceptualization. SS: Writing – review and editing, Writing – original draft, Project administration, Methodology. HM: Formal Analysis, Data curation, Writing – review and editing. JW: Validation, Writing – original draft, Formal Analysis. HW: Writing – original draft, Investigation. YS: Resources, Writing – review and editing, Validation, Writing – original draft.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research was funded by Xianyang City Key Research and Development Program (L2024-ZDYF-ZDYF-SF-0069), General Technology Program of Power China Northwest Engineering Corporation Limited (XBY-YBKJ-2023-20).
Conflict of interest
Authors QL and HM were employed by Power China Northwest Engineering Corporation Limited.
The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The authors declare that this study received funding from Power China Northwest Engineering Corporation Limited. The funder had the following involvement in the study: data collection and analysis, decision to publish.
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The author(s) declared that generative AI was not used in the creation of this manuscript.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fenvs.2025.1734277/full#supplementary-material
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Keywords: coal mining subsidence, soil anti-erodibility, loess slope, influence law, northernShaanxi coal mine area
Citation: Li Q, Song S, Ma H, Wu J, Wu H and Sun Y (2026) Effects of coal mining subsidence on soil anti-erodibility in the loess mining area of northern Shaanxi, middle reaches of the Yellow River. Front. Environ. Sci. 13:1734277. doi: 10.3389/fenvs.2025.1734277
Received: 29 October 2025; Accepted: 28 November 2025;
Published: 05 January 2026.
Edited by:
Haijun Qiu, Northwest University, ChinaCopyright © 2026 Li, Song, Ma, Wu, Wu and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Shijie Song, U29uZ3NoaWppZUB4dXN0LmVkdS5jbg==