Slope Scale Research Articles

Assessing rainfall-triggered landslides considering small-scale depth to bedrock uncertainty: A random field approach

Depth to bedrock (DTB) is a critical factor for rainfall–induced slope failures. However, the influence of uncertainties in these measurements, particularly at a small–scale, has not been fully understood. Numerical modeling was conducted to assess the impact of a variable bedrock topography on the stability of a real–world unsaturated slope. The simulations included a three–dimensional pore–water pressure estimation, derived from the numerical solution of the Richards equation, coupled with a slope stability assessment using numerical limit analysis. The study explored the potential of incorporating random fields (RFs) into an established DTB model to improve the understanding of rainfall–triggered landslides. The proposed methodology was applied to the analysis of a small watershed within the Papagaio River basin in Brazil, an area historically subjected to landslides triggered by rainfall events. Our main findings reveal that small variations in DTB can significantly impact the safety factor and probability of failure estimations. Furthermore, they influence the shape, location and failure volume associated to predicted landslides. The incorporation of RFs effectively addresses small–scale uncertainty in DTB, controls bedrock morphology, and enhances the assessment of probabilistic numerical modeling for landslide susceptibility. This study highlights the importance of accurate and comprehensive DTB characterization for assessing rainfall–induced landslides at local slope scale.

Exploring the inclusion of soil management practices in erosion models towards the improvement of post-fire predictions

Wildfires are recognized for having a strong impact on forest soils, a situation aggravated by inadequate pre-fire land management practices. Land management operations, such as plowing, are routinely carried out for cultural reasons and can impact soils for decades after their implementation. Therefore, it is crucial to take into account the pre-fire land management history when predicting post-fire sediment losses in burnt areas. This consideration is critical for a realistic assessment of soil erosion risk and, consequently, for effectively implementing emergency stabilization and/or rehabilitation measures.The aim of the study was to integrate pre-fire land management practices into erosion models, to enhance post-fire sediment losses predictions at slope scale. To accomplish this goal, both Multiple Linear Regression (MLR) and the revised-Morgan-Morgan-Finney model (revised-MMF) were applied in the Colmeal burnt area (Central Portugal). These models were adapted to account the impacts of different management options, specifically no plowing, downslope-plowing and contour-plowing, on the erosive response following a wildfire.The results revealed fluctuations in the performance of both models across different soil management, and over time since the wildfire. Despite the observed variability, it is important to highlight the positive outcomes achieved with the revised-MMF model over the three monitoring years where contour-plowing was applied. These results demonstrate that the best model performances are achieved when soil management is individualized and analyzed independently. Similarly, the MLR model exhibited improved performance when incorporating management practices into its predictions. This study confirms that disturbances on topsoil, whether caused by wildfires or soil management operations, play key roles in driving change in soil erosion. Hence, integrating these factors into models is essential for providing relevant information for the development of mitigation and/or restoration strategies in areas at high risk of erosion.

A slope scaling heuristic for the multi-period strategic planning of carbon capture and storage

Around the world, efforts are currently underway to implement various decarbonization strategies to meet net-zero emissions objectives. This includes carbon capture and storage (CCS), which involves capturing CO2 at emitter sites, and transporting it to geological reservoirs, where it is to be injected underground for long-term storage. In this work, we focus on the multi-period strategic planning of a CCS value chain involving pipeline CO2 transportation. From an Operations Research standpoint, this problem exhibits the characteristics of combined facility location and network design. To account for multiple scenarios of input parameters (e.g. market and geological variability), this problem has to be solved hundreds or thousands of times. Thus, reaching high-quality solutions quickly is crucial. As commercial solvers struggle to provide high-quality solutions under these time constraints, we propose a slope scaling heuristic based on previous work on single-period CCS planning and network design. This new heuristic approximates the cost of design variables, generates upper bounds via dynamic programming, uses a long-term memory search strategy, and includes a final improvement phase where a restricted model is solved. Computational experiments show that the proposed heuristic generates better solutions than CPLEX for most instances considered, at a fraction of the computational time.

Alpine plant communities and current topographic microrefugia vary with regional climates

Topographic microrefugia on slopes are assumed to be critical for the persistence of alpine plant species and the maintenance of alpine plant community diversity in a warming climate. They create microclimates, some of which are cooler and/or wetter than others, which may buffer continuing climate change. However, the current relationship of plant communities to microtopography at individual slope scale could differ among regional climates, and if so resilience in new climates would also differ.Vegetation cover and topographic site characteristics at a fine scale were recorded in the field in three alpine regions of the Rocky Mountains, USA: Glacier National Park, MT, the Indian Peaks Area, CO, and Taos Ski Valley, NM. Elements of alpine slopes were identified and transformed into ordinal variables. Two indicators of insolation were calculated from slope angle, slope aspect, and latitude, and soil depth indicators and elevation were recorded. In each region, the contribution of these variables to the variation in the plant community composition were compared using nonmetric multidimensional scaling and random forest models.The partitioned variance explained by the topographic and topography-derived climatic variables differed among the three regions. Variables related to moisture conditions were more important in the snowiest, northern region and the central region, while those related to energy were more important in the southern region with higher radiation and temperature. Lower correlations of mesoscale variables set microrefugia in a hierarchical context.The more extreme regional topographically derived climatic variables better explain the differentiation of alpine plant communities. These variables may not play the same role in potentially novel future climates. Because topographic features mediate regional climates to niche dimensions, setting microrefugia in a multiscale framework can focus research on climate change impacts.

The Influence of Rock Slope Scales of Joint Network and Slope Height on the Stability and Failure Mechanisms

This paper demonstrates the influence of slope geometry and scale of the joint networks on the stability and failure mechanisms in discontinued rock masses. These analyses are based on the finite element method (FEM) to calculate the factor of safety (FOS) and to simulate the explicit discontinuity deformations for different scales of rock masses. The study was carried out through examples of regular jointed models having different slope heights and irregular jointed dry rock slopes. Joints usually decrease the strength of the slopes and suggestively increase slope stability problems. The result shows that the slope stability decreases with increased block size and shape and that the irregular columnar joints are more unfavorable to the slope stability than the regular joints. Furthermore, with dropping the factor of safety and randomly distributed joints the rock failure mechanism appears to shift from structurally controlled for the 50 m slopes towards a step-like failure path for the 100 m and 200 m slopes.

3D Point Cloud and GIS Approach to Assess Street Physical Attributes

The present research explores an innovative approach to objectively assessing urban streets attributes using 3D point clouds and Geographic Information Systems (GIS). Urban streets are vital components of cities, playing a significant role in the lives of their residents. Usually, the evaluation of some of their physical attributes has been subjective, but this study leverages 3D point clouds and digital terrain models (DTM) to provide a more objective perspective. This article undertakes a micro-urban analysis of basic physical characteristics (slope, width, and human scale) of a representative street in the historic centre of Valencia (Spain), utilizing 3D laser-scanned point clouds and GIS tools. Applying the proposed methodology, thematic maps were generated, facilitating the objective identification of areas with physical attributes more conducive to suitable pedestrian dynamics. This approach provides a comprehensive understanding of urban street attributes, emphasizing the importance of addressing their assessment through advanced digital technologies. Moreover, this versatile methodology has diverse applications, contributing to social sustainability by enhancing the quality of urban streets and open spaces.

ERT-based experimental integrated approach for soil hydrological characterization in rainfall-induced shallow landslides prone areas

Shallow landslides triggered by heavy rainfalls are slope instabilities, developed in the most superficial eluvial layers, involving the first 2 m from the ground level. A crucial predisposing factor in shallow landslides occurrence is the soil water content, generally measured trough sensors installed in the first soil layers. However, despite being a very precise approach, this monitoring technique provides for a site-specific dataset. An integrated method to extend the hydrological characterization from site-specific to slope scale is presented, combining geotechnical analyses, field data monitoring, and geophysical investigations, in two experimental test sites located on Italian Apennines. Ten Electrical Resistivity Tomographies (ERT) of the first soil horizons were performed through different array geometries (2D-3D-Time-Lapse), calibrated and interpreted basing on stratigraphic logs, trenches, and monitored soil water content field data. The test sites colluvial covers composition was analyzed and compared to resistivity values to build conceptual hydrogeological models of the deep-water circulation. In addition, two time-lapse (4D) ERT surveys were performed in both test sites simulating very intense precipitations, to determine the resistivity variations at different soil drainage conditions, thus estimating the average bulk permeability. Bulk permeability can be also a useful input parameter for slope stability models, widely employed in engineering practices. This integrated method proved to be very useful for the hydrogeological characterization of the subsoil at slope scale, where it is susceptible to slope instability, improving the knowledge of water circulation, as well as the bulk permeability heterogeneities, which are shallow landslides triggering parameters.

Effects of soil erosion–deposition on corn yields in the Chinese Mollisol region

Soil erosion is a major challenge for crop production maintenance and improvement in agricultural regions worldwide. However, quantifying the impacts of soil erosion rate on crop yield has not been carried out often, and there are few reports on impacts of soil deposition crop yields, especially in the Chinese Mollisol Region. Thus, this study quantified soil erosion–deposition rates (SEDRs) at three agricultural catchments in the Chinese Mollisol region using the 137Cs technique and assessed soil erosion–deposition impacts on corn (Zea mays L.) yield. The results showed that SEDRs varied from −5471.7 (deposition) to 9956.0 (erosion) t km−2 yr−1. The distributions of both soil erosion and deposition in the three catchments were in coexistence, but soil erosion was dominant. In addition, above 2500 t km−2 yr−1 of soil erosion rates (larger than slight erosion rates) in the three catchments accounted for 41.0 %, indicating that soil erosion was severe. Moreover, corn yields in the three catchments ranged from 1.9 to 14.6 t ha−1. Compared with deposited sites, corn yields in eroded sites were 19.2 %–40.6 % lower. Furthermore, when soil erosion rates were moderate (2500–5000 t km−2 yr−1), corn yields were 32.4 % lower than those in non-eroded sites. The spatial distribution of corn yield was opposite to that of soil erosion rate at catchment and slope scales. The relationship between corn yields and soil erosion rates had a negative linear relationship (p < 0.01), which was validated with acceptable accuracy. There was a positive linear relationship between corn yields and soil deposition rates without statistical significance (p > 0.05). These findings are valuable for assessing how soil erosion–deposition affects crop yields to implement countermeasures for controlling soil erosion and maintaining sustainable agricultural development.

Snow mechanical property variability at the slope scale – implication for snow mechanical modelling

Abstract. Snow avalanches represent a natural hazard to infrastructure and backcountry recreationists. Risk assessment of avalanche hazard is difficult due to the sparse nature of available observations informing on snowpack mechanical and geophysical properties and overall stability. The spatial variability of these properties also adds complexity to decision-making and route finding in avalanche terrain for mountain users. Snow cover models can simulate snow mechanical properties with good accuracy at fairly good spatial resolution (around 100 m). However, monitoring small-scale variability at the slope scale (5–50 m) remains critical, since slope stability and the possible size of an avalanche are governed by that scale. To better understand and estimate the spatial variability at the slope scale, this work explores links between snow mechanical properties and microtopographic indicators. Six spatial snow surveys were conducted in two study areas across Canada. Snow mechanical properties, such as snow density, elastic modulus and shear strength, were estimated from high-resolution snow penetrometer (SMP) profiles at multiple locations over several studied slopes, in Rogers Pass, British Columbia, and Mt. Albert, Québec. Point snow stability metrics, such as the skier crack length, critical propagation crack length and a skier stability index, were derived using the snow mechanical properties from SMP measurements. Microtopographic indicators, such as the topographic position index (TPI), vegetation height and proximity, wind-exposed slope index, and potential radiation index, were derived from unoccupied aerial vehicle (UAV) surveys with sub-metre resolution. We computed the variogram and the fractal dimension of the snow mechanical properties and stability metrics and compared them. The comparison showed some similarities in the correlation distances and fractal dimensions between the slab thickness and the slab snow density and also between the weak layer strength and the stability metrics. We then spatially modelled snow mechanical properties, including point snow stability, using spatial generalized additive models (GAMs) with microtopographic indicators as covariates. The use of covariates in GAMs suggested that microtopographic indicators can be used to adequately estimate the variation in the snow mechanical properties but not the stability metrics. We observed a difference in the spatial pattern between the slab and the weak layer that should be considered in snow mechanical modelling.

Study of slope length (L) extraction based on slope streamline and the comparison of method results

Slope length is an important factor in soil erosion modeling, and the reasonable automatic extraction of slope length is of great significance in soil erosion research. However, previous studies have mainly focused on the regional scale, and how to effectively extract slope length at the slope scale deserves further research. In this study, a slope length extraction algorithm based on slope streamlines method (SSM) is proposed for the slope length extraction problem in geomorphology, and it is compared with three existing slope length calculation methods. The experimental results show that the new method can quickly calculate the length of slope streamlines, and the extracted slope lengths have better accuracy; the coefficients of determination demonstrates a better overall fitting effect of the four extraction methods, with coefficients of determination exceeding 0.7; this indicates that the use of SSM has similar accuracy and stability to other methods in calculating slope lengths. Among all the calculation methods, SSM has a better overall fitting effect for slope length calculation, and the obtained slope length value domain range is relatively small and concentrated in a small range, which expresses the slope length better.

Rock-mass heterogeneous rheological properties caused the formation of deep tension fractures

Tension failure is a unique phenomenon in solid Earth that occurs on scales ranging from large plate rift valleys to small laboratory rocks. On a slope scale, deep unloading tension fractures are distinct from conventional unloading fractures and are a unique geological phenomenon in valleys with high in-situ stress. To accurately reproduce the development and evolution of deep unloading tension fractures and to support major excavation projects, a series of works including geological investigation, laboratory tests, intrinsic model establishment, and numerical simulation were carried out in this study. The unloading rheological tests, accounting for time-dependent effects, uncover the heterogeneity in the rheological attributes of rock-mass strength parameters during valley downcutting. This heterogeneity manifests as a transition in rock-mass strength parameters that cohesion weakening-friction strengthening (CWFS). Drawing on the results of laboratory tests, a novel viscoelastic-plastic model, termed the WSR model, was proposed. This model takes into account both CWFS and rheological considerations. It has been applied to simulate deep unloading tension fractures in the Jinping I hydropower station (JP-I) and compared with conventional models. The results show that WSR model accurately reproduced the development and evolution of deep unloading tension fractures and the heterogeneity of rock-mass deformation during age evolution leads to the formation of deep unloading tension fractures. In this study, the rock-mass heterogeneous rheological properties were summarized as the heterogeneity of the rock-mass strength parameters during age deterioration and the heterogeneity of rock-mass deformation during age evolution; the WSR model was proposed to characterize the heterogeneous rheological property of rock-mass strength parameters and to reproduce the development and evolution of deep unloading tension fractures in the JP-I. This novel contribution to deep unloading tension fractures emphasizes that the rock-mass heterogeneous rheological properties lead to the formation of deep unloading tension fractures.

Spatial Distribution and Relationship between Slope Micro-Topography Changes and Soil Aggregate Stability under Rainfall Conditions

Natural rainfall affects the stability of soil aggregates by the kinetic energy of the rain changing the morphological characteristics of slope micro-topographic factors. Although the relationship between the stability of soil aggregates and micro-topography is not very significant at the slope scale, there are also rules to be found. This study aims to explore the relationship between slope micro-topography and aggregate stability, and to observe the spatial distribution of aggregate stability after water erosion. In this study, a digital elevation model of slope micro-topography was established by using a three-dimensional laser scanner to observe the slope erosion changes after rainfall events and clarify the spatial changes of soil aggregate stability and its relationship with slope micro-topography by combining geostatistics and generalized additive model (GAM). The results showed that the area of serious water erosion in the lower part of the slope accounted for 38.67% of the slope, and the micro-topography index of the slope changed obviously after rainfall, with the slope increasing by 3.1%, the surface roughness increasing by 5.34%, the surface cutting degree increasing by 26.67%, and the plane curvature decreasing by 61.7%. In addition, the GAM model was used to fit the multivariate variables. The results revealed that the slope and surface roughness were the key factors affecting the stability of water-stable aggregate. The slope and surface roughness were negatively correlated with the stability of water-stable aggregates.

Characterization of the Fels Landslide (Alaska) Using Combined Terrestrial, Aerial, and Satellite Remote Sensing Data

The characterization of landslides located in remote areas poses significant challenges due to the costs of reaching the sites and the lack of reliable subsurface data to constrain geological interpretations. In this paper, the advantages of combining field and remote sensing techniques to investigate the deformation and stability of rock slopes are demonstrated. The characterization of the Fels landslide, a large, slowly deforming rock slope in central Alaska, is described. Historical aerial imagery is used to highlight the relationship between glacier retreat and developing instability. Airborne laser scanning (ALS) and Structure-from-Motion (SfM) datasets are used to investigate the structural geological setting of the landslide, revealing a good agreement between structural discontinuities at the outcrop and slope scales. The magnitude, plunge, and direction of slope surface displacements and their changes over time are studied using a multi-temporal synthetic aperture radar speckle-tracking (SAR ST) dataset. The analyses show an increase in displacement rates (i.e., an acceleration of the movement) between 2010 and 2020. Significant spatial variations of displacement direction and plunge are noted and correlated with the morphology of the failure surface reconstructed using the vector inclination method (VIM). In particular, steeper displacement vectors were reconstructed in the upper slope, compared to the central part, thus suggesting a change in basal surface morphology, which is largely controlled by rock mass foliation. Through this analytical approach, the Fels landslide is shown to be a slow-moving, compound rockslide, the displacement of which is controlled by structural geological features and promoted by glacier retreat.

Study of Structural Morphology of Electrodeposited Ni Film

Structural morphology of thin electrodeposited metallic films plays a vital role in determining the properties of the films and their application. We prepared a range of Ni electrodeposited polycrystalline films using a BIOLOGIC potentiostat and investigated the effects of varying parameters such as the deposition rate and concentration of the solution to improve control over their properties. We conducted analysis of surface morphology of thin films of area 1cm2, as well as at microstructural level of area 50x50 um2, using ex-situ AFM and in-situ HS AFM. Ex-situ AFM data helps us to do quantitative surface analysis, including slope, scaling analysis [1] and grain area calculation as a function of time, concentration, and applied potential. HS AFM provides us with information about the grain structure evolution at microstructural level [2]. The texture of films was determined by XRD analysis. For the thin films, Ni[111] orientation was dominant, but for thick films, the dominant crystallographic orientations was Ni[200].We also performed EBSD analysis for Ni thin films after milling with focused ion beam. EBSD uses backscattered electron to obtain the information of structural morphology and crystallographic orientation of thin films layer by layer. The correlation between ex-situ AFM and EBSD data helps to gain a clear understanding of the structural features of the films. Liu, L., & Schwarzacher, W. (2013). Slope analysis and scaling analysis of electrodeposited thin films. Electrochemistry communications, 29, 52-54.Koorikkat, A., Payton, O., Picco, L., & Schwarzacher, W. (2020). Imaging the Surface of a Polycrystalline Electrodeposited Cu Film in Real Time Using In Situ High-Speed AFM. Journal of the Electrochemical Society, 167(16), 162510.

Soil Moisture Dynamics and Its Temporal Stability under Different-Aged Caragana korshinskii Shrubs in the Loess Hilly Region of China

Soil moisture has a great influence on vegetation growth and survival in arid and semiarid regions. Information about deep soil moisture dynamics is vital for restoring vegetation and improving land management on the water-limited Loess Plateau. The spatiotemporal dynamics and temporal stability of deep soil moisture (at a soil depth of 600 cm) were observed in situ under Caragana korshinskii shrubs that had various stand ages (named CK-10yr, CK-20yr and CK-35yr) in the Loess hilly region of China. The results showed that under C. korshinskii, soil moisture generally decreased as the stand age rose. Meanwhile, its moisture was consistent with precipitation variation, and an obvious time lag in soil moisture was found compared to that in precipitation during the entire growing season. Along the soil profile, a transition belt linking the shallow with deep soil moisture occurred at a 200 cm soil depth in different slope positions and aspects. At the slope scale, both the slope aspect and slope position significantly affected soil moisture variation in the areas with planted C. korshinskii shrubs, experiencing a decreasing trend from semi-shady slopes to sunny ones and from lower positions to upper ones. However, the variance in soil moisture between different positions and slope aspects was small. For the slope aspect, except for CK-20yr, the different-aged C. korshinskii shrubs had higher soil moisture content on sunny slopes than on semi-shady slopes at the upper 0–200 cm soil depth, while the opposite was true at the 200–600 cm soil depths. For slope positions, the soil moisture variation was small between the 0 and 200 cm soil depths and larger between the 200 and 600 cm soil depths. Within the whole profiles, the representative depth under the C. korshinskii shrubs for the soil moisture content was mainly concentrated between the 400–500 cm soil depths, on average, showing a gradual deepening trend with increasing restoration age. In summary, the findings indicate that natural recovery with low-water consumption grasslands and manual management measures, such as thinning and mowing, should be strengthened to minimize the high soil moisture consumption rates that occur in a healthy soil moisture environment and maintain sustainable vegetation restoration.

Detecting Recent Dynamics in Large-Scale Landslides via the Digital Image Correlation of Airborne Optic and LiDAR Datasets: Test Sites in South Tyrol (Italy)

Large-scale slow-moving deep-seated landslides are complex and potentially highly damaging phenomena. The detection of their dynamics in terms of displacement rate distribution is therefore a key point to achieve a better understanding of their behavior and support risk management. Due to their large dimensions, ranging from 1.5 to almost 4 km2, in situ monitoring is generally integrated using satellite and airborne remote sensing techniques. In the framework of the EFRE-FESR SoLoMon project, three test-sites located in the Autonomous Province of Bolzano (Italy) were selected for testing the possibility of retrieving significant slope displacement data from the analysis of multi-temporal airborne optic and light detection and ranging (LiDAR) surveys with digital image correlation (DIC) algorithms such as normalized cross-correlation (NCC) and phase correlation (PC). The test-sites were selected for a number of reasons: they are relevant in terms of hazard and risk; they are representative of different type of slope movements (earth-slides, deep seated gravitational slope Deformation and rockslides), and different rates of displacement (from few cm/years to some m/years); and they have been mapped and monitored with ground-based systems for many years (DIC results can be validated both qualitatively and quantitatively). Specifically, NCC and PC algorithms were applied to high-resolution (5 to 25 cm/px) airborne optic and LiDAR-derived datasets (such as hillshade and slope maps computed from digital terrain models) acquired during the 2019–2021 period. Qualitative and quantitative validation was performed based on periodic GNSS surveys as well as on manual homologous point tracking. The displacement maps highlight that both DIC algorithms succeed in identifying and quantifying slope movements of multi-pixel magnitude in non-densely vegetated areas, while they struggle to quantify displacement patterns in areas characterized by movements of sub-pixel magnitude, especially if densely vegetated. Nonetheless, in all three landslides, they proved to be able to differentiate stable and active parts at the slope scale, thus representing a useful integration of punctual ground-based monitoring systems.

Plot-based study to evaluate raindrop detachment capacity on moss-dominated biocrusted slope under simulated rainfall with different intensities

Biocrusts play a critical role in prevention of erosion, but little is known on the relationship between biocrust cover and raindrop detachment capacity at the slope scale. Evaluating the raindrop detachment capacity on biocrusted slope is essential for better knowledge of the rainfall-induced erosion of biocrusted slope. Thus, laboratory simulated rainfall experiments were conducted on plots (140 × 120 cm) representing moss-dominated biocrusted slopes to measure the amounts of raindrop detachment under a complete combination of different biocrust cover (0%, 20%, 40%, 50%, 60%, and 80%) and rainfall intensities (42, 60, 90, 120, and 150 mm h−1) at 26.79% slope gradient with two replications. The results showed that the biocrust cover, rainfall intensity, and their interaction all significantly affected the raindrop detachment modulus (RDm). The RDm in biocrust plot was significantly lower than in bare soil plot under rain events with the same rainfall intensities. The lower biocrust cover or the larger rainfall intensities led to higher RDm. Reduction benefit of raindrop detachment modulus (RB-RDm) were greater than its corresponding biocrust cover values. When the biocrust cover increased from 20% to 40%, the increase range and growth trend of RDm decreased with increasing rainfall intensity. Our results indicated that the development of biocrusts on slope is an effective way of reducing raindrop detachment by protecting soil in their covered area and increasing flow depth. When moss-dominated biocrust cover reached 40%, the raindrop detachment capacity effectively weakened even under rain events with large rainfall intensities. These findings may conducive to offer a scientific guidance for soil erosion control in the Loess Plateau and in other arid and semiarid regions.

Influence of Different Mining Damage Types on Soil Erodibility in Coal Mining Areas of Northern Shaanxi in the Middle Reaches of the Yellow River in China

The middle reaches of the Yellow River basin are not only rich in coal resources in China, but are also a typical experimental field for studying the law and mechanism of soil erosion caused by coal mining in the area. Grasping the differences in soil’s physical and chemical properties caused by different types of mining damage and then analyzing the differences in soil erosion is conducive to achieving ecological environmental protection and high-quality development in coal mining areas, thus improving soil and water conservation efficiency and saving costs. In this study, we took the typical loess subsidence slope of Ningtiaota mine field in the northern Shaanxi coal mining area as the research object, collected the soil samples at different slope positions, and measured the soil mechanical composition and organic matter mass fraction using an MS2000 laser particle size analyzer and a total organic carbon analyzer, respectively. Based on the EPIC model, the soil erodibility K value was further calculated, the spatial variation characteristics of the soil’s mechanical composition and organic matter mass fraction were analyzed, and the soil erosion effect under different mining damage types was interpreted. The results are as follows: ① The subsidence of loess slope and the development of mining ground fissures will reduce the clay mass fraction and increase the sand mass fraction in the shallow soil on the slope. The clay mass fraction of the whole slope will decrease by 4.50–30.30%, and the soil sand mass fraction will increase by 6.83–23.67%. The shallow soil at the top and middle of the slope has obvious sandy characteristics, and the amount of sandy soil in the crack area of the same slope is obviously higher than that in the non-crack area. Slope position is the main reason to control the shallow soil sand on the slope of loess subsidence in the northern Shaanxi coal mining area. ② The subsidence of loess slope and the development of mining ground fissures will lead to a decrease in organic matter mass fraction in shallow soil in different amounts. The decrease in organic matter mass fraction in the whole slope is 12.68–35.46%, and the decrease in organic matter mass fraction in shallow soil at the top and middle of the slope is significant, and the loss of organic matter in the crack area of the same slope is obviously higher than that in the non-crack area. The greater the width of the mining ground fissures and the smaller the horizontal distance from ground fissures, the more organic matter mass fraction in shallow soil will decrease. Mining ground fissures are the main factors when it comes to controlling the loss of organic matter in the shallow soil on the loess subsidence slope in northern Shaanxi coal mining area. ③ The negative correlation coefficients of shallow soil erodibility K value with the soil clay mass fraction and organic matter mass fraction all exceeded 0.6, a significant level, and there is a high degree of consistency in the change characteristics of the slope scale. The subsidence of the loess slope and the development of the mining ground fissures will have the effect of improving the erodibility of shallow soil in all parts of the slope. The erodibility of shallow soil at the top and middle of the slope increases significantly, and the erodibility of shallow soil in the crack area of the same slope is obviously higher than that in the non-crack area. The larger the width of the mining ground fissures and the smaller the horizontal distance from the ground fissures, the higher the erodibility of the surrounding shallow soil. After calculation, it was found that the maximum boundary of the mining ground fissures developed on the loess subsidence slope in northern Shaanxi coal mining area to improve the erodibility of the surrounding shallow soil was 115 cm, and the main action range was concentrated within 90 cm. These research results can provide a scientific basis for accurate prevention and control of the soil erosion effect of mining subsidence in loess coal mining in the area of northern Shaanxi, thus saving costs.

Slope Scaling Effect and Slope-Conversion-Atlas for Typical Water Erosion Regions in China

Slope has obvious scale-dependent characteristics and it changes with the change in DEM resolution, which brings uncertainty to the evaluation process of regional resource and environment. In this paper, one typical county in each of the six water erosion regions in China was selected as the sample area, respectively. Based on DEM data of ALOS DEM, ASTER GDEM and SRTM DEM with different spatial resolutions, slope characteristics, such as gradient, eigenvalue, frequency and cumulative frequency curves, were calculated by using the third-order inverse distance square weighted difference algorithm, to explore the ability of depicting terrain by these three DEM data. Based on the idea of geo-information map, the “surface-slope conversion atlas” under different resolutions was constructed to achieve the grading correction of slope extraction under low resolution. The results showed that: (1) with the resolution of DEM decreases, the slope information of each area tends to be more generalized and gradually concentrated. The slope frequency curve gradually changed from “tall and thin” to “short and fat”, and the peak of the cumulative frequency curve moved to the low-slope area. Six sample areas showed different degrees of slope reduction. (2) In the process of slope grading correction, except for Maoxian, the proportion of low-resolution results converted to medium and low slope grades (0°–25°) is large. (3) The slope spectrum conversion method has a good correction effect on the errors generated by the slope extraction results of DEM90 and DEM30, and the correction rates reached 80% and 90%, respectively. A slope conversion atlas can effectively improve the expression ability of low-resolution DEM data on topography, which can provide a basis for regional resource and environment evaluation, and territorial space optimization.

Scale Effect of Sloping Landscape Characteristics on River Water Quality in the Upper Reaches of the Si River in East-Central China

Landscape composition and configuration determine the source of pollutants. They also determine the interception and pollution-holding potential of the surface landscape. Using the upper reaches of the Si River Basin, a major grain-producing region in Shandong province in east-central China, as a case study, this study analyzed the influence of landscape characteristics on river water quality (RWQ) after superimposing topographic slope factors for 2017, and investigated which spatial scale had the strongest influence on RWQ. The landscape indices of three spatial scales (riparian zone, river reach and sub-catchment) and three slope scales (general land, flat ground and steep slope) were extracted. Correlation analysis and redundancy analysis were used to reveal the effects of landscape characteristics on RWQ at different scales. The results indicate that the landscape types were dominated by arable land and construction land in 2017. Landscape indices at different scales were significantly different. The RWQ generally met Class II or III surface water quality standard. Arable land and construction land had a negative impact on RWQ, both of which were “source” landscapes, while forest was a “sink” landscape that can effectively alleviate the deterioration of RWQ. The eight landscape indices which indicated heterogeneity, fragmentation level, landscape diversity, and shape information had different degrees of correlation with NO3−-N, NH4+-N, CODMn and BOD5. Different scales of landscape features had different correlations with RWQ, with the strongest correlation in the riparian zone, followed by the river reach, and the weakest in the sub-catchment. The influence of steep slope land was higher than that of flat ground land. The study confirmed that landscape structure and configuration had a scale effect on RWQ. It thus has great significance for water resources protection and land use management in the study area.