Search Results (306)

Background/Objectives: This cross-sectional study aimed to estimate the Locally Estimated Scatterplot Smoothing (LOESS)-smoothed percentiles for growth trajectories and evaluate age-related tendencies across groups using visual cross-sectional graphs. Methods: A total of 1147 patient records were analyzed, including 648 females and 469 males aged 5–20 years, with a mean age of 11.9 (SD ± 3.8) years. Twenty-seven cephalometric variables were organized into six measurement domains: cranial base, maxillary complex, mandibular complex, occlusal plane, vertical relationship, and sagittal relationship. Percentile curves were generated using LOESS regression across an age range of 5–20 years. Results: The LOESS-smoothed curves showed age-related trends across age groups. An upward trend in the curves was observed for the anterior and posterior cranial bases between 5 and 12 years of age, a plateau indicating reduced age-related change across groups during mid-adolescence. Maxillary measurements showed a similar pattern, with a clear upward tendency during childhood and reduced age-related change after approximately 12 years. Mandibular length and projection showed increasing trends during childhood, followed by a plateau or reduced slope across later age groups. The occlusal plane and vertical dimensions showed consistent patterns that approached a plateau around 12 years, indicating minimal age-related differences between groups. Changes in the ANB angle and Wits appraisal reflected a progressive forward tendency of the mandible across childhood age groups, followed by reduced age-related change during adolescence. Conclusions: These findings suggest that many craniofacial measurements show an upward trend during childhood followed by a plateau or reduced age-related change across age groups between approximately 12 and 14 years. The percentile-based growth curves presented here offer a practical reference for clinicians to evaluate craniofacial growth trajectories as population-level approximations derived from cross-sectional data in the pediatric population. Full article

Soil erosion and nutrient loss degrade the soil resource base and water quality in dryland agricultural landscapes, yet optimal design of vegetation buffers for soil conservation under intensifying rainfall remains poorly quantified, particularly for nutrient retention. This study is novel in integrating event-scale rainfall-simulation experiments, Bayesian hierarchical modelling, Causal Forest analysis, and WEPP simulations to quantify how the sequential addition of biocrusts and grasses to shrub buffers shifts density thresholds for runoff, soil loss, and nutrient export across varying rainfall intensities. Experiments were conducted across a continuous shrub-density gradient (0–11,429 plants ha⁻¹) representing three configurations: shrub monoculture, shrub-biocrust, and shrub-biocrust-grass on agricultural hillslopes of the Chinese Loess Plateau. Runoff, soil loss, and exports of total nitrogen (TN) and total phosphorus (TP) were measured. Results demonstrate three main findings. First, multilayer shrub–biocrust–grass buffers exhibited lower soil loss than monocultures. Posterior estimates indicate reductions from approximately 3.8 t ha⁻¹ at moderate monoculture density to below 1.0 t ha⁻¹ at lower planting densities, with 94% of the highest-density intervals reflecting uncertainty in these estimates. Second, Causal Forest analysis reveals a functional separation of controls: rainfall intensity dominates soil loss (88% importance) and runoff (84%), whereas nutrient retention responds more strongly to buffer structure and density management. Third, WEPP simulations across rainfall intensities (50–180 mm h⁻¹) and slopes (10–30%) identify an optimal multilayer buffer density of 3800–5700 plants ha⁻¹, which delivers robust multifunctional benefits with 50–67% lower planting requirements than conventional high-density monocultures. These findings demonstrate that multilayer vegetation buffers enhance soil retention and reduce nitrogen and phosphorus losses from hillslopes, sustaining the soil resource base and protecting water quality in dryland agricultural landscapes. The integrated modelling framework provides transferable, evidence-based density recommendations for climate-resilient soil conservation in similar dryland regions. Full article

Assessing the construction suitability and sediment reduction potential of dry-farming wide terraces is critical for improving soil and water conservation in semi-arid and semi-humid regions, yet these aspects are seldom evaluated within an integrated framework. Focusing on the Loess Plateau, this study delineates potential construction areas based on precipitation constraints, quantifies soil erosion using the Revised Universal Soil Loss Equation, and develops a multidimensional framework to jointly evaluate construction suitability and sediment reduction potential on sloping farmland. Results indicate that slope, transportation accessibility, and soil erosion intensity are the primary determinants of suitability. Highly suitable, suitable, and marginally suitable areas account for 7.5%, 7.2%, and 4.3% of the study area, respectively, with Shanxi, Shaanxi, and Gansu provinces—and particularly Yulin, Yan’an, and Qingyang—emerging as priority regions for implementation. Scenario analysis suggests that targeting (i) highly suitable and suitable areas or (ii) all suitable classes would reclaim approximately 59.89 × 10³ km² and 77.19 × 10³ km² of sloping farmland, respectively, leading to reductions in mean soil erosion modulus of 16.6% and 22%. These findings provide a quantitative basis for optimizing terrace deployment and advancing regionally targeted soil erosion mitigation strategies on the Loess Plateau. Full article

Accurate spatial identification of check dams is a key prerequisite for evaluating soil and water conservation benefits and optimizing dam system planning on the Loess Plateau. Current deep learning models face severe misclassification and omission issues under complex terrain due to the scarcity of check dam samples and the lack of prior geographic knowledge. This study proposes a recognition method based on Faster R-CNN, constrained by suitable areas and microtopography. The Xiliugou watershed in Inner Mongolia was selected as the study area. Based on Google Earth imagery and field survey data, a check dam sample dataset was constructed, integrating the morphological features of “linear dam body with a trapezoidal slope.” Using the construction suitable area constraints defined by the Technical Specifications for Check Dams and microtopography standard deviation (δ) derived from DEM as dual spatial filtering mechanisms, these were deeply embedded into the Faster R-CNN model to limit the search space and enhance geographic plausibility. Experimental results show that the constrained Faster R-CNN model achieved a precision and recall of 92.86% and 96.89%, compared with the accuracy rate of only deep learning model recognition (60.61%), which significantly increased by 32.25%, indicating that geographical constraints have an enhancing effect. Using this method, a total of 191 embankment dams were identified in the Xiliugou Basin. New 30 unrecorded embankment dams (21 small dams and 9 micro-dams) were discovered. The model’s good generalization ability was verified in the Han Tiechuan geographical isolation area, which contained 153 embankment dam samples, with an accuracy rate of 72.94%. Spatial analysis further revealed the “successive interception along tributaries” distribution pattern and strong spatial aggregation characteristics (box dimension D ≈ 0.36) of check dams in the Xiliugou watershed. This study confirms the critical role of suitable area and microtopography constraints in improving the accuracy and reliability of deep learning models and provides a transferable technical paradigm for automated, high-precision surveys of regional soil and water conservation projects. Full article

Sediment connectivity is a key indicator of whether eroded sediment can be efficiently transported within a catchment. Landslides are a major form of rainfall-induced erosion on the steep slopes of the Loess Plateau and contribute substantially to overall catchment sediment yield. However, evaluating the connectivity of landslide-derived sediment and its implications for sediment transport risk remains challenging. Therefore, field investigations were conducted in three watersheds (R1, R2, and R3) on the Loess Plateau to examine landslides triggered by rainstorms. We analyzed the characteristics of landslide erosion and its influencing factors, applied graph theory to investigate sediment connectivity after landslides occurred, and assessed the risk of sediment transport to the catchment outlet. The results showed that the landslide number densities in the catchments R1, R2, and R3 were 9, 155, and 214 km⁻², respectively. The average erosion intensities were 25,153, 53,074, and 172,153 t km⁻², respectively. The network analyses indicated that the locations of landslides within the catchments were primarily concentrated in areas with high transport networks and high sediment accessibility to the catchment outlets. The sediment connectivity index further showed that 59%, 43%, and 51% of landslides in the three watersheds, respectively, were at high risk of delivering sediment to the catchment outlet. Accordingly, measures such as slope drainage and gully dam construction may help reduce both landslide occurrence and sediment transport. These findings provide new insights into the transport risk of eroded sediment from a connectivity perspective, identify hotspot areas of sediment connectivity and landslide erosion, and support the targeted prevention and control of catchment erosion. Full article

This study focuses on the 1718 Tongwei earthquake (magnitude 7.5) and investigates the four counties of Tongwei, Gangu, Wushan, and Qin’an. By combining field surveys of earthquake damage and historical landslide data, we employed statistical analysis models to select ten influencing factors related to topography, geology, and seismic activity in the study area. We utilized kernel density analysis tools to statistically assess the number, area, and density of landslide points within different ranges of each influencing factor, identifying the most susceptible factor ranges for loess landslides triggered by the earthquake. The spatial distribution of these landslides under varying influences was visualized. Principal component analysis was conducted to explore the dominant factors affecting the spatial distribution of loess landslides, focusing on strongly correlated factors such as elevation, slope, and distance to rivers to further investigate their coupling effects. The results indicate that loess landslides are concentrated at elevations of 1300–1900 m, slopes of 10–20°, with a terrain fluctuation of 0–30 m, distances to rivers of 1200–1600 m, and proximity to active faults of 2–8 km, predominantly in grassland and farmland areas on south-facing slopes. Full article

Under global climate change, analyzing carbon storage dynamics and their drivers is essential for understanding regional carbon sink capacity. Human activities and land-use change have substantially affected regional carbon storage. However, in China, most existing studies emphasize specific driving pathways, and integrated analyses of the combined effects of climate, natural, human, and landscape factors remain limited. This study aims at clarifying the integrated mechanisms by which multiple driving factors influence regional carbon storage. The InVEST model was used to analyze the carbon storage spatiotemporal changes. OPGD was then applied to evaluate the explanatory power of driving factors and their interactions, quantifying their contributions to carbon storage spatial patterns. Based on PLS-SEM, the direct and indirect effects of LULC, climate, natural, human, and landscape factors were quantified to elucidate the driving pathways of carbon storage. This study focuses on Shaanxi Province, which is a key ecological restoration region in the core area of the Loess Plateau. The main results are as follows: (1) From 2000 to 2020, carbon storage in Shaanxi Province showed a continuous increasing trend, rising from 2.97 × 10¹⁰ Mg C to 3.03 × 10¹⁰ Mg C. (2) LULC was identified as the most important direct and predominantly negative driving factor of carbon storage. (3) Natural factors had a strong positive influence on carbon storage, among which slope and NDVI exhibited the highest explanatory power; in contrast, climate factors showed weaker but still positive effects. (4) Human activities affected carbon storage through both direct and indirect pathways associated with LULC, with positive effects driven by landscape factors and negative effects driven by natural factors, while climate factors exhibited mixed but weak effects. Overall, carbon storage dynamics in Shaanxi Province reflect a hierarchical and path-dependent process shaped by the combined effects of natural constraints, human activities, and policy guidance through LULC pathways, providing important evidence for systematically understanding the driving structure and pathways of regional carbon storage. These findings highlight the importance of aligning land-use policies with regional biophysical constraints to enhance carbon sequestration efficiency. Full article

Clarifying the relationship between landscape patterns and runoff coefficient, along with identifying key influencing pathways, is crucial for formulating sustainable water resource management strategies. Since the launch of the Grain-for-Green (GfG) project in 1999, the landscape pattern of the Loess Plateau has been profoundly reshaped, altering regional rainfall-runoff processes. Assessment across 27 catchments selected in the central Loess Plateau demonstrated forest and grassland areas expanded by 738.8 km² and 480.4 km², respectively, paralleled by a 20.1% enhancement in vegetation coverage. Correspondingly, surface runoff decreased by 28.1–90.6% in the 2000s and 12.8–95.5% in the 2010s compared to the 1960s, with a similar decline in runoff coefficient. This study further developed a novel landscape unit mapping method, integrating vegetation coverage, land use, slope, and soil type to compute landscape metrics. Partial least squares regression (PLSR) and piecewise structural equation modeling (piecewiseSEM) were constructed to systematically analyze the linkage between landscape patterns and surface runoff. The constructed landscape metrics explained 64.6% of the variance in the runoff coefficient, with perimeter area fractal dimension (PAFRAC), mean perimeter-area ratio (PARA_MN), and aggregation index (AI) exerting significant influence. The findings provide a scientific basis for water resource management in regions with similar environmental characteristics. Full article

Rainfall-induced shallow loess landslides pose a significant threat to human life and property. Early warning and risk assessment of these landslides are critical prerequisites for engineering control and disaster loss reduction. The Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS)-Three-dimensional Slope Stability Analysis Tool (Scoops 3D) joint model can overcome the shortcomings of using a single TRIGRS model for hydrological analysis and a single Scoops 3D model for slope stability analysis. Landslide risk assessment based on expected economic loss, on the other hand, can overcome the issue of maintaining the risk level edge and sorting at the same level. In this paper, the TRIGRS model’s head pressures were put into the Scoops 3D model, with the southeast of Fangta, a town in Shaanxi province, China, as the study area. The relationship between the slope gradient and the number of grids in each stable grade was certified. The rainfall thresholds for landslides, based on both rainfall intensity and rainfall duration, were obtained by rerunning the TRIGRS-Scoops 3D joint model. The landslide range and land uses of each dangerous slope were determined by maximum likelihood classification, and then the expected economic loss was calculated. To verify the reliability of the TRIGRS-Scoops 3D joint model, the identified dangerous slopes were compared with the results from landslide susceptibility mapping. The results show that the unstable grids are concentrated within a slope gradient of 30° to 35°, and the landslide early warning levels are divided into Tier 3, Tier 2, and Tier 1 Warnings. The occurrence of shallow loess landslides is affected by both rainfall intensity and rainfall duration, and the combined effect should be considered in early warning. The distribution of both extreme susceptible grids and high susceptible grids across all 23 dangerous slopes demonstrates the reasonableness of the TRIGRS-Scoops 3D joint model. The landslide susceptible probability within some dangerous slopes exhibits spatial variability. The mapping relationship between the slope gradient and loess landslides is extremely complex. This paper can provide a theoretical basis for the early warning and risk management for rainfall-induced shallow loess landslides; the proposed method is also applicable to other regions with similar geological and meteorological conditions. Full article

Long-term ecological monitoring is essential for sustainable management in fragile regions. This study assessed four decades (1986–2024) of ecological evolution in the Ji River Basin—a 1276.64 km² transitional loess–gully ecosystem in China’s Yellow River Basin—using the Remote Sensing Ecological Index (RSEI). We integrated multi-temporal Landsat images via Google Earth Engine to construct a 40-year RSEI time series. The index couples greenness (NDVI), wetness (WET), heat (LST), and dryness (NDBSI) through principal component analysis, with PC1 explaining > 82% of the variance. Three evolutionary phases were identified: initial degradation (1986–1996), driven by slope cropland expansion; stabilization (1996–2006), coinciding with early ‘Grain for Green’ policies; and sustained recovery (2006–2024), characterized by the expansion of high-quality zones. We developed a novel resilience zoning framework integrating local spatial consistency, terrain constraints, and functional state (mean RSEI 2016–2024), which delineated three zones: high-resilience refugia (19.37%), moderate-resilience matrix (75.54%), and low-resilience corridors (5.09%). Mid-slope positions (TPI: 1.220–1.510) within moderate-resilience zones demonstrated optimal restoration efficiency, challenging conventional uniform approaches. The findings advocate spatially differentiated strategies—investing in transitional zones, retrofitting degraded corridors, and monitoring stable refugia—to advance the implementation of Sustainable Development Goal 15 in semi-arid regions globally. Full article

Research on the evolutionary patterns and propagation mechanisms of different drought types is of great significance for regional water resources management and the prevention and control of agricultural drought risks. Taking the arid region in the western Chinese Loess Plateau as the study area, this paper systematically revealed the spatiotemporal variation characteristics, propagation lag time and conditional probability of meteorological and agricultural droughts based on the monthly Standardized Precipitation Evapotranspiration Index (SPEI) and self-calibrating Palmer Drought Severity Index (scPDSI) during 1985–2022 by comprehensively adopting the Mann–Kendall trend test, Sen’s slope estimation, run theory, drought frequency analysis, as well as the Copula function and event-matching method. The results showed that during the study period, meteorological drought (characterized by SPEI) exhibited an insignificant intensification overall, while agricultural drought (characterized by scPDSI) presented a significant mitigation at the monthly scale. The maximum occurrence frequency of agricultural drought reached 70.39%, which was significantly higher than that of meteorological drought (38.82%); in addition, agricultural drought featured a longer average duration and greater severity, with a spatial pattern of higher in the northwest and lower in the southeast in the study area. The average propagation lag time of drought derived from the Copula function was 1.41 months, versus 2.19 months obtained by the event-matching method. When meteorological drought reached the moderate level (SPEI < −1.0), it was likely to trigger agricultural drought of mild or higher severity. The research findings can provide a scientific reference for formulating differentiated drought prevention strategies in the arid region of the western Loess Plateau, China. Full article

The mechanical behavior of loess under varying moisture conditions plays a critical role in the stability of slopes and foundations in loess regions. Owing to its high porosity and metastable structure, loess is particularly sensitive to moisture-induced strength degradation. Although geogrid reinforcement has been widely adopted to improve soil stability, the combined influence of moisture condition, reinforcement characteristics, and confinement on the shear behavior of loess remains insufficiently understood. In this study, consolidated undrained (CU) triaxial tests were conducted on partially saturated loess reinforced with glass fiber geogrids (GFGs) and basalt fiber geogrids (BFGs) under different moisture contents (13–17%) and confining pressures (100–300 kPa). The effects of geogrid type, reinforcement configuration, and confinement on shear strength and deformation behavior were systematically examined. The results indicate that geogrid reinforcement significantly enhances the shear strength, stiffness, and ductility of loess, particularly under low to moderate confining pressures. Increasing the number of reinforcement layers resulted in peak strength improvements of up to approximately 25% and promoted a transition from brittle to ductile behavior. Distinct reinforcement responses were observed: GFG exhibited higher initial stiffness and more rapid mobilization, whereas BFG demonstrated progressive tensile mobilization and superior residual strength. Furthermore, a modified Unified Twin-Shear Strength Theory (UTSST) incorporating a strain-dependent reinforcement mobilization coefficient was proposed, which provided an empirical representation of the observed strength evolution with good agreement with the experimental results (R² > 0.96). Full article

Understanding the crack development and rainfall infiltration in loess under wetting–drying cycles is crucial for assessing slope stability and promoting sustainable land management in ecologically vulnerable regions. This study employed a three-dimensional column model (Φ₂₄ × 50 cm) with 64 buried electrodes to simulate short-term heavy rainfall by changing the light duration (10 h/d and 5 h/d) and using 100 mm rainfall water. Results indicate that dry–wet cycles cause cumulative damage, significantly altering soil infiltration properties. After four cycles, the rainfall infiltration recharge coefficient increased from an initial 0.44% to 45.58%, a more than 100-fold rise. Resistivity imaging revealed a shift in water transport mode: from uniform matrix flow initially to preferential flow dominated by crack networks as cracks developed. During drying, crack zones exhibited high resistivity (ρ > 150 Ω·m), while water-filled cracks during infiltration showed low resistivity (ρ < 50 Ω·m). Resistivity is an excellent comprehensive index to quantify multi-field coupling damage, and its change (ρ∝ 1/w^1.86 × 1/(1 + 0.032 width)) synchronously responds to water content, crack development and dry–wet process. Low water content (w < 15%) and medium crack width (4–6 mm) are the most sensitive states. Longer illumination (10 h/d) promoted greater crack development and higher infiltration capacity compared to shorter cycles (5 h/d). The developed resistivity–moisture relationship provides a non-destructive monitoring tool for slope moisture dynamics, supporting not only geotechnical stability assessment but also optimized irrigation scheduling and adaptive land-use planning. These insights contribute directly to the sustainable management of soil and water resources in loess landscapes, aligning with sustainability goals in fragile ecosystems. Full article

To promote the application of wrap-around reinforced soil structures in high-intensity seismic regions, this study systematically investigated the influence of different wrap-around facing types on the seismic performance of reinforced loess slopes. Through shaking table model tests, the dynamic responses of three wrap-around facing types—C-shaped wrap-around facing, secondary-reinforcement wrap-around facing, and self-wrap facing—under the excitation of two seismic waves (El Centro wave and Wenchuan Wolong wave) were compared and analyzed. The test introduced the marginal spectrum energy analysis method to accurately identify the location and evolution process of slope damage. The results indicated that reinforcement significantly enhances the global integrity of the slope, yet the influence of the wrap-around facing type on seismic performance is significant. The C-shaped wrap-around facing exhibited the best global stability and seismic performance, with damage initiating inside the slope body and a good energy dissipation mechanism. The secondary-reinforcement wrap-around facing is prone to stress release and local loosening in the slope crest region due to weak constraints. The self-wrap facing has insufficient restraint at the top, where the reinforcement tends to experience pullout. Compared with the El Centro wave, the Wolong wave, rich in long-period components, induced stronger dynamic responses, resulting in greater slope face displacement, acceleration amplification, marginal spectral amplitude, and reinforcement strain. Significant damage in the slopes initiated in the mid-upper region, and the damage pattern was directly related to the wrap-around facing type. The research findings provide a theoretical basis for the optimal design of reinforced loess slopes in high-intensity seismic zones. Full article

Frequent extreme rainfall events in northwestern China have made loess–mudstone composite slopes highly susceptible to progressive failure, posing serious threats to infrastructure and public safety. This study investigates the deformation–failure mechanisms and evolutionary characteristics of such slopes under rainfall infiltration by integrating indoor physical model tests with long-term SBAS-InSAR time-series deformation monitoring. The physical model experiments reveal pronounced hydro-mechanical heterogeneity within the composite slope: surface fissures act as preferential flow paths, the mudstone interface exerts a significant water-blocking effect, and hydrological responses differ markedly between shallow and deep layers. The wetting front exhibits a distinct dual-layer migration pattern, characterized by rapid lateral expansion in the shallow layer and delayed advancement in the deep layer. Rainfall infiltration induces a progressive failure process, evolving from toe infiltration softening and mid-slope local erosion to differential crest erosion and ultimately overall sliding, forming a typical failure pattern of frontal creeping, central shearing, and rear tensile deformation. SBAS-InSAR results indicate that the natural landslide experienced a similar long-term progressive evolution, developing from shallow, localized deformation to deep-seated and slope-wide acceleration under multi-year rainfall. Despite differences in spatial deformation patterns influenced by natural microtopography, the failure stages and dominant deformation zones identified by both approaches show strong consistency. The combined results demonstrate that rainfall-induced suction decay, interface softening, pore water pressure accumulation, and stress redistribution jointly control the progressive instability of loess–mudstone slopes. This study highlights the effectiveness of integrating physical modeling and InSAR monitoring for elucidating rainfall-induced landslide mechanisms and provides scientific insights for hazard assessment and mitigation in composite-structure slopes. Full article