Search Results (163)

Water erosion is a critical degradation process that reduces fertility and agricultural sustainability, especially in semi-arid regions. The Universal Soil Loss Equation (USLE) allows for the quantification of this phenomenon using factors such as rainfall erosivity (R) and topography (length-slope, LS). In this study, both factors were estimated and analyzed in the Cañitas sub-basin, located in the semi-desert area of the state of Zacatecas, Mexico, characterized by irregular precipitation and limited data availability. The objective of this study is to estimate and analyze the R factor and LS factor to evaluate their influence on soil water erosion processes. Records from five meteorological stations (1986–2022) were used, along with the Modified Fournier Index (MFI) and Geographic Information Systems (GIS) tools, generating spatial maps of rainfall erosivity and topography. An average R factor of 81.69 MJ∙mm/ha∙h∙year was estimated, consistent with the values obtained using the MFI. The LS factor shows that the northwestern area of the study zone has the most extensive and steepest slopes (up to 20). This study analyzes the R and LS factors to identify areas vulnerable to water erosion and to understand the influence of climate and topography in a semi-arid region, which can serve as a reference for planning conservation actions and managing watersheds in semi-arid areas with high climatic variability. Full article

This study aimed to identify areas at risk of deforestation in the Cerrado biome of the Brazilian Midwest (states of Mato Grosso, Mato Grosso do Sul, and Goiás) and to estimate potential soil losses due to water erosion under land-use change scenarios. The methodology integrated the Universal Soil Loss Equation (USLE), spatializing rainfall erosivity (R), soil erodibility (K), topographic factor (LS), and cover-management factor (CP), with the ACEU (Accessibility, Cultivability, Extractability and Unprotected/protection status) model to assess deforestation risk based on accessibility, agricultural suitability, extractive activities, and legal protection status. Results indicated an average soil loss of 0.11 t ha⁻¹ year⁻¹ under natural vegetation cover, with 90% of the area presenting losses below 0.25 t ha⁻¹ year⁻¹. However, 27.5% of the remaining natural cover is located in areas classified as high or very high deforestation risk, indicating significant environmental vulnerability. Simulated scenarios of land-use conversion to pasture and annual crops revealed substantial increases in soil loss, particularly under annual cropping systems, potentially exceeding soil loss tolerance thresholds across millions of hectares. The findings demonstrate that integrating deforestation risk assessment with erosion modeling is a strategic tool for environmental planning, reinforcing the importance of preserving native vegetation to maintain ecosystem services and ensure long-term environmental sustainability. Full article

Deep stormwater drainage tunnels are increasingly being used to mitigate urban flooding, but in-tunnel sediment deposition reduces their discharge capacity and complicates their maintenance. With direct field observation constrained, numerical simulation is essential, and river-based total sediment load formulas require reassessment for use in deep tunnels. The three-phase (air–water–sediment) CFD solver SedInterFoam is first validated against a benchmark open-channel suspended sediment experiment, and is then applied to a horseshoe tunnel under a fixed design discharge for multiple inlet sediment concentrations spanning urban stormwater conditions. Four classical formulas (Yang, Shen–Hung, Ackers–White, Engelund–Hansen) are evaluated at the CFD-resolved hydraulic state; Toffaleti is omitted because its zone-based formulation is incompatible with the partially filled horseshoe geometry. The CFD consistently shows persistent retention of a substantial fraction of the inlet sediment load, whereas the transport capacity-limited interpretation of the classical formulas predicts near-complete sediment throughput—indicating structural inadequacy for the dilute, supply-limited regime typical of urban stormwater. A Universal Soil Loss Equation (USLE)-style dimensionless deposition formula is therefore proposed, with inlet sediment loading as the explicit independent variable and a tunnel correction factor $K_{tunnel}$ absorbing the geometric, hydraulic, and sediment variations. Its regression yields an almost linear scaling and a nearly constant deposition ratio, while analysis of the internal flow and concentration fields shows that the retained sediment is strongly concentrated near the bed and that near-bed turbulent mixing weakens moderately with a rising inlet concentration. While calibrated for a single non-cohesive settleable sand fraction, the framework provides a transferable basis for inlet-loading-dependent deposition prediction in deep stormwater drainage tunnels, and subsequent extension of $K_{tunnel}$ to broader sediment conditions with field-based validation is expected to enable maintenance planning, dredging volume estimation, and sediment retention risk assessment. Full article

Apical prolapse, a common form of Pelvic Organ Prolapse (POP), is often linked to weakened support structures such as the uterosacral (USL) and cardinal ligaments (CL), influenced by factors like vaginal childbirth, aging, and obesity. Although surgical mesh use is expected to increase, the Food and Drug Administration (FDA) banned polypropylene mesh for transvaginal anterior compartment prolapse in 2019 due to safety concerns, highlighting the need for alternatives such as biodegradable implants. This study developed four biodegradable mesh implants (square and sinusoidal geometries) mimicking the USL and CL. These were applied within a computational pelvic model to assess biomechanical behavior during the Valsalva maneuver and to explore different fixation methods (continuous, interrupted and simple stitch sutures). Baseline analysis of the healthy model established vaginal displacement under normal conditions. Without implant support, complete CL rupture increased displacement by 34%, and complete USL rupture raised displacement by 69%. Polycaprolactone implants consistently reduced anterior vaginal wall displacement in all impairment scenarios. Square implants mimicking the USL reduced displacement by up to 10% in cases of complete USL rupture with intact CL. Similarly, square implants mimicking the CL reduced displacement by up to 15% with complete CL rupture and healthy USL. Simulations with both ligaments impaired showed that USL contribute to support, while CL play a key role in stabilization. These findings demonstrate the potential of biodegradable implants to enhance POP repair. However, further studies are needed to evaluate long-term degradation and clinical applicability. Full article

Land leveling deep-seated landslides for agricultural use alters soil profile integrity and soil functionality. In the mid-20th century, such interventions in the Transylvanian Basin (Romania) involved grading and converting landslide bodies into arable land. This study evaluates the consequences of interventions on soil physicochemical properties and erosion susceptibility in the case of two deep-seated landslides. Soil samples collected from leveled landslide bodies were analyzed for pH, total nitrogen, available phosphorus (P-AL), available potassium (K-AL), calcium carbonates, humus content, and texture. The results, in the case of the two studied deep-seated landslides, indicate contrasts between areas where the Ah horizon is preserved and where leveling exposed the C horizon or parental material at the surface. Exposed zones exhibit reduced nitrogen and humus content, altered textures, and higher carbonate influence, indicating lower fertility potential despite 65 years of pedogenesis. Spatial assessment using Sentinel-2-derived NDMI and USLE-based erosion modelling confirms increased moisture stress and higher erosion susceptibility in areas with exposed substratum. These findings demonstrate that the leveling of the two studied deep-seated landslide bodies, although effective in expanding arable surfaces, leads to persistent soil degradation patterns and reduced agro-ecological resilience. Sustainable cultivation of such terrains requires targeted soil conservation measures, including erosion control and adapted land management practices. The results provide important implications for land-use planning in landslide-prone agricultural landscapes. Full article

Accurate modeling of dam reservoir sedimentation is crucial for effective reservoir management. Traditional approaches for estimating sedimentation include the Hydraulic Approach (HA) and the Empirical Approach (EA). HA involves complex computations and requires substantial data, while the EA relies on equations like the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE), which use subjective parameters and lead to inaccurate estimations. This study introduces a novel approach called the hydrological approach, which integrates the sediment rating curve (SRC) and the dam reservoir elevation-capacity curve (ECC) to estimate reservoir sedimentation and evolution of the ECC. This HA leads to a newly developed equation for the estimation of the sediment rise and the corresponding sediment volume. The approach is applied to the Wadi Fatimah Dam in Saudi Arabia. By combining rainfall data from 1985 to 2022 and performing rainfall–runoff hydrological modeling combined with the proposed HA, sediment accumulation trends and reservoir capacity reductions are estimated from past to present. Validation through ground survey and geophysical investigations in 2008 confirms model accuracy. Findings reveal significant sediment buildup, with an estimated average of 7.5 m rise from 1985 to 2008. The study’s main findings highlighted the urgent need for effective sediment management strategies in arid regions, where sedimentation rates are notably higher than in other regions. Full article

Soil erosion is a growing environmental problem in arid regions, where land-use changes and landscape fragmentation directly influence land degradation. This study estimated soil loss in the Tarabillas sub-basin, located in the Chihuahuan Desert, Mexico. To this end, the Universal Soil Loss Equation (USLE) was applied and integrated with Geographic Information System (GIS) tools. Landsat TM and OLI satellite imagery were classified through supervised techniques, achieving overall accuracies above 89%. The analysis was supported by comparing erosion patterns associated with land-use changes occurring during the 1990–2021 period, assessed through cross-tabulation matrices and landscape metrics. The results show that although the average erosion potential of the sub-basin remained constant at approximately 12.45 t ha⁻¹ yr⁻¹, erosion redistributed spatially, concentrating in areas where agriculture has replaced natural vegetation. Shrublands and grasslands continue to dominate the high erosion categories due to their wide spatial extent and high erodibility. These findings highlight that fragmented agricultural expansion constitutes the main driver of landscape transformation and soil vulnerability, emphasizing the importance of integrating remote sensing, GIS, and empirical models to support sustainable land management in arid regions. Full article

Clogging is the main mechanism that deteriorates the hydraulic functionality of permeable pavements, particularly in porous asphalt mixtures (PAM). This study evaluated the hydraulic impact of sediments from three peri-urban micro-watersheds in the Boyacá region of Colombia on the infiltration capacity of PAM. Road infrastructure and drainage conditions were analysed using orthophotos and field inspections to identify geomorphological factors that favour sediment transport toward the roadway. Annual erosion rates were estimated using the Universal Soil Loss Equation (USLE), and sediments were characterized both within the watersheds and at their outlet onto the road. Hydraulic performance was assessed through laboratory tests using a Falling Head Permeameter, complemented by field infiltration measurements with a Modified Cantabrian Infiltrometer (0.25 m²). Results showed erosion rates of up to 7.9 t/ha·year and infiltration losses above 90% under clogged conditions. A partial hydraulic recovery of around 40% was observed after maintenance, particularly when sediments exhibited a higher sand fraction. These findings demonstrate that combining USLE-based erosion modelling with controlled hydraulic testing provides a robust framework for evaluating clogging risks in peri-urban roads and offers new evidence on the hydraulic behaviour of PAM exposed to non-urban sediments in the design and maintenance of sustainable pavements. Full article

Unsupervised visible–infrared person re-identification (USL-VI-ReID) plays a pivotal role in cross-modal computer vision applications for intelligent surveillance and public safety. However, the task remains hampered by large modality gaps and limited granularity in feature representations. In particular, channel augmentation (CA) is typically used only for data augmentation, and its potential as an independent input modality remains unexplored. To address these shortcomings, we present a multimodule collaborative USL-VI-ReID framework that explicitly treats CA as a separate input modality. The framework combines four complementary modules. The Person-ReID Adaptive Convolutional Block Attention Module (PA-CBAM) module extracts discriminative features using a two-level attention mechanism that refines salient spatial and channel cues. The Varied Regional Alignment (VRA) module performs cross-modal regional alignment and leverages the Multimodal Assisted Adversarial Learning (MAAL) to reinforce region-level correspondence. The Varied Regional Neighbor Learning (VRNL) implements reliable neighborhood learning via multi-region association to stabilize pseudo-labels and capture local structure. Finally, the Uniform Merging (UM) module merges split clusters through alternating contrastive learning to improve cluster consistency. We evaluate the proposed method on SYSU-MM01 and RegDB. On RegDB’s visible-to-infrared setting, the approach achieves Rank-1 = 93.34%, mean Average Precision (mAP) = 87.55%, and mean Inverse Negative Penalty (mINP) = 76.08%. These results indicate that our method effectively reduces modal discrepancies and increases feature discriminability. It outperforms most existing unsupervised baselines and several supervised approaches, thereby advancing the practical applicability of USL-VI-ReID. Full article

The availability of water resources has significantly decreased in recent years. Therefore, it is essential to design comprehensive management strategies at the watershed level. This study included a methodological novelty by combining morphometric analysis with multicriteria analysis to prioritize sub-watersheds in the Las Flores Watershed (LFW), located in Chiapas, Mexico. The LFW catchment area covers 2517.96 km² and was divided into 29 sub-watersheds. Morphometric analysis, based on physical characteristics (shape, stream network, and relief), allows us to infer the level of susceptibility to erosion of a watershed. However, to improve the prioritization of sub-watersheds, the erosion rate (EA) was estimated using the Universal Soil Loss Equation (USLE), as well as rainfall intensity and curve number. The results show that sub-watersheds SW₂₀ and SW₁₅ have the highest predicted EA values, that is, 234.76 and 222.10 t ha⁻¹, respectively. The final prioritization framework established that the sub-watersheds classified as very high priority were SW₂₀, SW₂₈, SW₁₅, SW₂₁, and SW₀₉, covering an area of 734.19 km², corresponding to 29.16% of the total area of LFW. Therefore, in these sub-watersheds, the immediate implementation of water regulation structures and conservation practices is required to minimize their susceptibility to water erosion. Full article

Soil erosion undermines the sustainable development of land—a vital resource for human survival. Research into the spatiotemporal dynamics of soil erosion is therefore crucial for formulating effective soil and water conservation strategies and advancing ecological protection efforts. In the domain of soil erosion research, the Universal Soil Loss Equation and Revised Universal Soil Loss Equation (USLE/RUSLE) model represent the dominant approach for quantifying soil erosion volumes. While this methodology yields reliable outcomes, it fails to incorporate an assessment of the relative significance of the factors embedded within the model. This study selected the Henan section of the Yellow River Basin as the research area, using monthly remote sensing data from 2010 to 2025 as the main data source. Taking into account factors such as rainfall, slope, elevation, vegetation coverage, and hydrological conservation measures, the RUSLE model was used to calculate and combine Geographic Information System (GIS) geographic detectors for quantitative analysis of soil erosion factors. The results showed the following: (1) The average soil erosion modulus in the study area from 2010 to 2025 was mainly micro and mild erosion. (2) Soil erosion exhibits a certain periodicity, with a year of significant soil erosion occurring every 3–4 years. The overall trend of soil erosion is a decrease. (3) Geographic detector analysis shows that slope has the greatest impact on soil erosion, with larger slopes leading to more severe soil erosion. The influence of each factor ranges from large to small as slope > water conservation measures > rainfall > vegetation coverage > elevation. (4) The interaction between factors can enhance the influence on soil erosion, and the interaction between vegetation cover factors and other factors significantly increases the influence; after interacting with various factors, the slope factor will significantly increase the influence of soil erosion. The research results can provide technical support and decision-making basis for ecological protection in the Yellow River Basin, such as through soil and water conservation, returning farmland to forests, and slope greening; The dominant factors and obvious interaction factors in the research area can provide a scientific basis for subsequent scholars to optimize the parameters of regional models. Full article

The Mun River Basin, the largest Mekong tributary in Northeast Thailand, has experienced extensive agricultural expansion and forest decline, raising concerns over increasing soil erosion and sediment transfer. This study provides an integrated assessment of soil loss, sediment yield (SY), and sediment delivery ratio (SDR) across 19 sub-watersheds using the Universal Soil Loss Equation (USLE), field-based SY data, and multivariate statistical analyses in 2024. Basinwide soil loss was estimated at ~35 million t y⁻¹ (mean 4.96 t ha⁻¹ y⁻¹), with more than 80% of the basin classified in the no erosion to very low erosion classes. Despite substantial hillslope erosion, only 402,405 t y⁻¹ of sediment reaches the river network, corresponding to a low SDR of 1.15%, which falls within the range reported for large tropical watersheds with significant reservoir infrastructure. Soil loss is most strongly influenced by slope and forested terrain, while SY responds primarily to rainfall and tree plantations; urban land, croplands, and reservoirs act as sediment sinks. Principal Component Analysis (PCA) resolved multicollinearity and produced six components explaining over 90% of predictor variance. A PCA-based regression model predicted SY per unit area with high accuracy (r = 0.81). The results highlight the dominant roles of hydroclimate and land-use structure in shaping sediment connectivity, supporting targeted soil and watershed-management strategies. Full article

Soil erosion remains a critical global concern, yet long-term catchment-scale assessments that explicitly link historical land-use transitions with erosion responses remain limited. This study evaluates how ±240 years record of historical and projected land-use changes influence soil erosion in the Myjava Basin by integrating parcel-level land-use reconstructions from 1787 to 2030 into a distributed USLE-2D framework. R, K, and parcel-based C and P factors were temporally standardized, and LS was derived using an ensemble of four widely applied algorithms. A PCA was applied to quantify the relative contribution of RUSLE factors across time, and all analyses were performed within a reproducible geospatial modelling environment. The results indicated a long-term decline in total erosion of ±78% at the landscape scale and ±60% within arable land from the 19th century to the present, driven mainly by a major reduction in arable land (from ±62% to ±37%) and expansion of forest and shrub vegetation. Despite this decline, persistent hotspots remain concentrated on steep upland slopes with high LS (>10%), while agricultural parcels experienced erosion rates 10–20 times higher than the basin-wide mean across all periods. PCA shows that LS and rainfall erosivity dominate erosion variability (PC loadings ±0.78–0.84), while C and P factors increase in influence in recent and projected periods, contributing up to ±40% of total explained variance. These findings demonstrate that long-term land-use transitions have substantially reduced basin-scale erosion risk. Full article

Rainfall characteristics proven to trigger general erosive events (EE) and rill erosion events (RE) under reference experimental conditions of soil type, slope, and land use—previously established at a test site in central Italy—are applied as likely thresholds to characterize their spatiotemporal variability across Umbria using 24 years of semi-hourly data from 53 stations. Marked spatial patterns emerge, with mean EE frequencies per station ranging from 1.14 to 2.36 per month, while mean RE frequencies per station vary between 0.04 and 0.45 per season. No significant temporal trends are observed over the study period. Monthly and seasonal comparisons between EE and RE frequencies often deviate from the corresponding USLE R-factor dynamics, highlighting limitations of relying solely on this parameter. These findings are contextualized within common soil conservation practices—such as cover crops—to identify critical periods during which maintaining soil cover. For example, winter—when cover crops are typically present in Central Italian agroecosystems—is among the seasons with the highest EE frequency (4.45 yr⁻¹), second only to autumn (6.47 yr⁻¹). However, when focusing on REs, winter shows the lowest mean frequency (0.08 yr⁻¹). In contrast, the mean RE frequency increases in summer (0.24 yr⁻¹) and reaches its maximum in autumn (0.26 yr⁻¹), when bare soil or poorly developed cover crops are common. Overall, results provide actionable insights for aligning protective measures with high-impact erosive event probabilities. Full article

The cover-management factor (C-factor) plays a pivotal role in soil erosion control and is the most easily influenced by policymakers. Despite the availability of numerous C-factor estimation methods, systematic comparisons of their applicability and associated uncertainties remain limited, particularly for future projections under climate change scenarios. This study systematically evaluates multiple widely used C-factor estimation models and projects potential C-factor changes under future scenarios up to 2070, using 2015 as a baseline. Results reveal substantial spatial variability among models, with the land use/land cover-based model (CLu) showing the strongest correlation with the reference model (r = 0.960) and the lowest error (RMSE = 0.048). Using the CLu model, global average C-factor values are projected to increase across all Shared Socioeconomic Pathways–Representative Concentration Pathways (SSP-RCP) scenarios, rising from 0.077 to 0.079–0.082 by 2070. Statistically significant trends were observed in 28.0% (SSP1-RCP2.6) and 26.6% (SSP5-RCP8.5) of global land areas, identified as hotspot regions (HRs). In these HRs, mean C-factor values are expected to increase by 16.1% and 33.4%, respectively, relative to the 2015 baseline. Economic development analysis revealed distinct trajectories across income categories. Low-income countries (LICs, World Bank classification) exhibited a pronounced dependency on development pathways, with C-factor values decreasing by −50.3% under SSP1-RCP2.6 but increasing by +95.8% under SSP5-RCP8.5 compared to 2015. In contrast, lower-middle-income, upper-middle-income, and high-income countries exhibited consistent C-factor increases across all scenarios. These variations were closely linked to cropland dynamics, with cropland areas in LICs decreasing by 64.6% under SSP1-RCP2.6 but expanding under other scenarios and income categories between 2015 and 2070. These findings highlight the critical importance of sustainable land-use policies, particularly in LICs, which demonstrate the highest magnitude of both improvement and degradation under varying scenarios. This research provides a scientific foundation basis for optimizing soil conservation strategies and land-use planning under future climate and socioeconomic scenarios. Full article