Search Results (113)

Wildfires, whether natural or human-caused, significantly alter soil properties and increase soil erosion susceptibility, particularly through changes in rill detachment capacity (Dc). This study aimed to evaluate the influence of fire intensity on key soil properties and to recognize their relationships with Dc under controlled laboratory conditions. The research was conducted in the Darestan Forest, Guilan Province, northern Iran, a region characterized by a Mediterranean semi-arid climate. Soil samples were collected from three fire-affected conditions: unburned (NF), low-intensity fire (LF), and high-intensity fire (HF) zones. A total of 225 soil samples were analyzed using flume experiments at five slope gradients and five flow discharges, simulating rill erosion. Soil physical and chemical characteristics were measured, including hydraulic conductivity, organic carbon, sodium content, bulk density, and water repellency. The results showed that HF soils significantly exhibited higher rill detachment capacity (1.43 and 2.26 times the values compared to the LF and NF soils, respectively) and sodium content and lower organic carbon, hydraulic conductivity, and aggregate stability (p < 0.01). Strong correlations were found between Dc and various soil properties, particularly a negative relationship with organic carbon. The multiple linear equation had good accuracy (R² > 0.78) in predicting rill detachment capacity. The findings of the current study show the significant impact of fire on soil degradation and rill erosion potential. The study advocates an urgent need for effective post-fire land management, erosion control, and the development of sustainable soil restoration strategies. Full article

Accurate microtopography data are an important input for characterizing small-scale rill erosion and its progression following disturbances. UAV–LiDAR systems are increasingly accessible and have successfully been used to measure microtopography data for several applications. Yet, the use of UAV–LiDAR systems for rill erosion studies in post-landslide landscapes have not been well investigated. Therefore, the purpose of this study was to implement and evaluate a UAV–LiDAR-based workflow to capture the microtopography of a post-landslide landscape, and by doing so, to help to determine best practices for UAV–LiDAR-based rill analysis. A commercial UAV–LiDAR system was used to map three post-landslide slopes and generate digital elevation models with a 1 cm-per-pixel ground resolution. Using data captured over multiple years, temporal rill development was assessed by comparing rill cross-sections and calculating changes to rill density and erosion volume. A flow-accumulation algorithm was adopted to automatically extract the rill network. We found that a flow accumulation algorithm with a threshold value of 5000 detected the rill network with overall accuracies of >88% and F1-scores of >93%. Vertical cross-sections of individual rills revealed an increase in the depth and width of rills over a one-year period. This study demonstrates that a commercial UAV–LiDAR system can effectively describe microtopography in a post-landslide landscape and facilitate analysis of small-scale rill characteristics and the progression of rill erosion. Full article

Soil erosion affects land productivity, water quality, and ecosystem resilience. Traditional monitoring methods are often time-consuming, labor-intensive, and resource-demanding, while unmanned aerial vehicles (UAVs) provide high-resolution, near-real-time data, improving accuracy. This study conducts a bibliometric analysis of UAV-based soil erosion research to explore trends, technologies, and challenges. A systematic review of Web of Science and Scopus articles identified 473 relevant studies after filtering for terms that refer to types of soil erosion. Analysis using R’s bibliometrix package shows research is concentrated in Asia, Europe, and the Americas, with 304 publications following a surge. Multi-rotor UAVs with RGB sensors are the most common. Gully erosion is the most studied form of the issue, followed by landslides, rills, and interrill and piping erosion. Significant gaps remain in rill and interrill erosion research. The integration of UAVs with satellite data, laser surveys, and soil properties is limited but crucial. While challenges such as data accuracy and integration persist, UAVs offer cost-effective, near-real-time monitoring capabilities, enabling rapid responses to erosion changes. Future work should focus on multi-source data fusion to enhance conservation strategies. Full article

Straw incorporation is applied in sloping farmland to coordinate soil water, fertilizer, air, heat, and soil erosion control in soil loss areas. Straw incorporation is considered to significantly affect soil detachment. However, the knowledge about the influence of soil consolidation by rainfall and mechanical effect by straw incorporation in short-term on soil detachment capacity (Dc) by rill flow is still limited. The current study was carried out to quantify the impact of soil consolidation by rainfall and mechanical effect under straw incorporation on Dc. The soil samples were collected from seven different plots (straw incorporation rates of 0 (CK), 0.2, 0.4, 0.6, 0.8, and 1.2 kg m⁻² with rainfall simulation of 30 mm and without straw incorporation and rainfall simulation (CK0)) and subjected to flume scoring experiments. The results indicated that the Dc with different straw incorporation rates significantly differed and decreased by 39.16–60.04%, compared with CK. The Dc exhibited a power function relationship with hydraulic parameters and stream power was the most appropriate hydraulic variable to express Dc for different straw incorporation rates. The hydraulic characteristics, straw incorporation rates, and interaction between them have a significant impact on the Dc, and Dc was more sensitive to hydraulic characteristics. The contribution rates to Dc reduction benefits by soil consolidation exceeded those by mechanical effect of incorporated straw. The impact of incorporated straw with rainfall simulation in short-term on Dc has a threshold of a straw incorporation rate of 0.4 kg m⁻². The Dc for different straw incorporation rates could be satisfactorily simulated using the composite equation of binary power-exponential function of stream power and soil cohesion. This research reveals the impacts of soil consolidation by rainfall and the mechanical effect of incorporated straw on Dc, and offers a framework for predicting and managing soil erosion in areas susceptible to soil loss. Full article

The advent of geomatic techniques and novel sensors has opened the road to new approaches in mapping, including morphological ones. The evolution of a land portion and its graphical representation constitutes a fundamental aspect for scientific and land planning purposes. In this context, new paradigms for geomorphological mapping, which are useful for modernizing traditional, geomorphological mapping, become necessary for the creation of scalable digital representation of processes and landforms. A fully remote mapping approach, based on multi-source and multi-sensor applications, was implemented for the recognition of landforms and processes. This methodology was applied to a study site located in central Italy, characterized by the presence of ‘calanchi’ (i.e., badlands). Considering primarily the increasing availability of regional LiDAR products, an automated landform classification, i.e., Geomorphons, was adopted to map landforms at the slope scale. Simultaneously, by collecting and digitizing a time-series of historical orthoimages, a multi-temporal analysis was performed. Finally, surveying the area with an unmanned aerial vehicle, exploiting the high-resolution digital terrain model and orthoimage, a local-scale geomorphological map was produced. The proposed approach has proven to be well capable of identifying the variety of processes acting on the pilot area, identifying various genetic types of geomorphic processes with a nested hierarchy, where runoff-associated landforms coexist with gravitational ones. Large ancient mass movement characterizes the upper part of the basin, forming deep-seated gravity deformation, highly remodeled by a set of widespread runoff features forming rills, gullies, and secondary shallow landslides. The extended badlands areas imposed on Plio-Pleistocene clays are typically affected by sheet wash and rill and gully erosion causing high potential of sediment loss and the occurrence of earth- and mudflows, often interfering and affecting agricultural areas and anthropic elements. This approach guarantees a multi-scale and multi-temporal cartographic model for a full-coverage representation of landforms, representing a useful tool for land planning purposes. Full article

Kinanthropometry is the study of body dimensions and composition measurements, which are influenced by factors such as age and nutritional status, establishing a relationship between static measurements and dynamic performance. This study aimed to evaluate the kinanthropometric differences among 403 individuals (aged 18–42), categorized by biological sex and the recreational sport they practiced. The main objective of this study was to clarify whether or not there were statistically significant differences between these groups. All of the measurements and indices were obtained following the International Society for the Advancement of Kinanthropometry (ISAK) protocol. Significant differences were found in most variables among the different sports. In general, the men showed higher values in terms of weight, height, body circumference, body mass index (BMI), relative index of the lower limbs (RILLs), percentage of muscle mass (%M), and percentage of residual mass (%R). The women exhibited higher values in terms of skinfold thicknesses, Cormic index (CI), body density index (BDI), percentage of fat mass (%F), and percentage of bone mass (%B). These findings can guide individuals in selecting sports based on their morphotype, optimizing their physical performance in recreational activities and improving their health and quality of life. Full article

Empirically based approaches, like the Universal Soil Loss Equation (USLE), are appropriate for estimating mass movement attributed to rill erosion. USLE and its associates become widespread even in spatially extended studies in spite of its original plot-level concept, as well as with certain constraints on the supply of suitable input spatial data. At the same time, there is a continuously expanding opportunity and offer for the application of remote sensing (RS) imagery together with machine learning (ML) techniques to model and monitor various environmental processes utilizing their versatile benefits. The present study focused on the applicability of data-driven geospatial models for predicting soil erosion in three vineyards in the Upper Pannon Wine Region, Central Europe, considering the seasonal variation in influencing factors. Soil loss was formerly modeled by USLE, thus providing non-observation-based reference datasets for the calibration of parcel-specific prediction models using various ML methods (Random Forest, eXtreme Gradient Boosting, Regularized Support Vector Machine with Linear Kernel), which is a well-established approach in digital soil mapping (DSM). Predictions used spatially exhaustive, auxiliary, and environmental covariables. RS data were represented by multi-temporal Sentinel-2 satellite imagery data, which were supplemented by (i) topographic covariates derived from a UAV-based digital surface model and (ii) digital primary soil property maps. In addition to spatially quantifying soil erosion, the feasibility of transferring the inferred models between nearby vineyards was tested with ambiguous outcomes. Our results indicate that ML models can feasibly replace the empirical USLE model for erosion prediction. However, further research is needed to assess model transferability even to nearby parcels. Full article

Global sensitivity analysis (GSA) of the revised universal soil loss equation (RUSLE) factors is in its infancy but is crucial to rank the importance of each factor in terms of its non-linear impact on the soil erosion rate. Hence, the goal of this study was to perform a GSA of each factor of RUSLE for a soil erosion assessment in southern Bahia, Brazil. To meet this goal, three non-linear topographic factor (LS factor) equations alternately implemented in RUSLE, coupled with geographic information system (GIS) software and a variogram analysis of the response surfaces (VARSs), were used. The results showed that the average soil erosion rate in the Pardo River basin was 25.02 t/ha/yr. In addition, the GSA analysis showed that the slope angle which is associated with the LS factor was the most sensitive parameter, followed by the cover management factor (C factor) and the support practices factor (P factor) (CP factors), the specific catchment area (SCA), the sheet erosion (m), the erodibility factor (K factor), the rill (n), and the erosivity factor (R factor). The novelty of this work is that the values of parameters m and n of the LS factor can substantially affect this factor and, thus, the soil loss estimation. Full article

Water erosion is a significant global threat due to the high soil loss rate and all its consequent implications. Technologies to predict erosion are strongly related to measurements and vice versa. Measurements can simply provide empirical evidence of the erosion process and are hard to extrapolate in time and space. Measurements were used to develop some erosion models, such as the Universal Soil Loss Equation (USLE), and also for their calibration and validation. Several measurement techniques are used to collect soil erosion data at different spatial and temporal scales, but they cannot be considered fully accurate in any experimental condition. Each technique exhibits advantages and disadvantages, so extensive knowledge of their feasibility, accuracy, and limitations is required to correctly plan experiments and use the performed measurements. In this paper, recent scientific developments on the measurement of rainfall erosivity, soil loss at the plot scale, and rill and gully erosion using close-range photogrammetry are presented. Further considerations are made on the quality of soil erosion measurements and the usefulness and importance of measuring plot soil loss. Our critical analysis highlighted that the techniques reported in the literature are a solid basis, which, however, should be developed to improve their range of applicability and data quality. Full article

Rill erosion is a major issue on a global scale, and predicting the presence, position, and development of erosive forms on hillslopes is a significant challenge for the scientific community. Several plot-scale investigations confirmed the reliability of the terrestrial photogrammetric (TP) technique for studying rill erosion and the reliability of a method for extracting the rill network from Digital Surface Models (DSMs) and measuring the corresponding volume. In this paper, for an intense erosive event that occurred at the Sparacia experimental area (Sicily, Southern Italy), TP surveys of three plots, with different length and steepness, incised by rills, were performed to reconstruct the DSMs. For each plot, the rill network was extracted from the DSMs, and the non-contributing network was distinguished from the contributing one, from which the soil loss and the consequent eroded volumes V were determined. The specific aims were to (i) establish the effect of plot steepness on rill depths and some morphometric characteristics of the drainage rill network; (ii) test and calibrate the relationship between V and the total rill length L, using all rill measurements available in the literature and those obtained in this study; and (iii) modify the V–L relationship by including climate forcing and assessing the related performance. The rill depths, h, the drainage frequency, and drainage density of the rill networks detected in the three plots were compared. The analysis demonstrated that h and the morphometric parameters of the contributing rill network increase with plot steepness s. In particular, the mean depth increases from 2.79 to 4.85 cm for slope increasing from 14.9 to 26%. Moreover, the drainage frequency of the contributing rill network varies from 0.16 m⁻² for s = 14.9% to 0.47 m⁻² for s = 26%, while the drainage density of the contributing rill network varies from 0.92 m⁻¹ for s = 14.9% to 2.1 m⁻¹ for s = 26%. Finally, using the data available in the literature and those obtained in this investigation, an empirical relationship between V and the total rill length L was firstly tested and then rearranged considering the event rainfall erosivity R_e. Including R_e in the rearranged equation guaranteed the best performance in V estimation. Full article

Rill erosion, mostly affecting steep and long hillslopes, is one of the most severe effects of deforestation and wildfires in natural ecosystems. Specific monitoring and accurate but simple models are needed to assess the impacts of these forest disturbances on the rill detachment process. To address this need, this study has simulated the rill detachment capacity (D_c) through flume experiments on samples of soils collected in hillslopes after deforestation and severe burning. The associations between D_c and organic matter (OM) and the aggregate stability of soil (WSA), two key parameters influencing the rill detachment process, have also been explored under the two soil conditions (deforested and burned soils) using multivariate statistical techniques. Finally, linear regression models to predict D_c from these soil parameters or the hydraulic and morphological variables (water flow rate, WFR, and soil slope, S), set in the flume experiments, have been proposed for both soil conditions. Higher D_c in samples from deforested sites compared to the burned soils (+35%) was measured. This D_c increase was associated with parallel decreases in OM (−15%) and WSA (−34%) after deforestation compared to the wildfire-affected sites. However, the discrimination in those soil properties between the two soil conditions was not sharp. Accurate linear equations (r² > 0.76) interpolating D_c and the shear stress (τ) have been set to estimate the rill erodibility (K_r) to evaluate soil resistance in erosion models to be applied in deforested or burned sites. Full article

Rill swell (RS) events are outflows of dry, fine-grained material mainly observed at drawpoints in cave mining. These events can negatively affect production and have fatal consequences. Unfortunately, comprehensive studies analyzing these events are lacking. This paper uses the discrete element method to study RS events. With this method, a numerical model was constructed and calibrated based on an RS event recorded in Ridgeway Deeps Block Cave. Drawpoint geometries, material properties, and the initial mass of the fine material were then analyzed. The results show that both the brow beam height and drawpoint width had a noticeable influence on the RS magnitude, mainly on the tonnage of the flow and the distance reached by coarse particles dragged into the extraction drift. While the mass of fine material is crucial to the magnitude of RS events, results suggest that narrowing drawpoint width and/or increasing brow beam height can mitigate the impact of RS events. Full article

Terrace erosion has become increasingly pronounced due to the rising incidence of heavy rainfalls resulting from global climate change; however, the processes and mechanisms governing erosion of loess terraces during such events remain poorly understood. A field investigation was performed following a heavy rainfall event in the Tangjiahe Basin to examine the soil erosion characteristics of loess terraces subjected to heavy rainfall events. The results show that various types of erosion occurred on the terraced fields, including rill, gully, and scour hole in water erosion, and sink hole, collapse, and shallow landslide in gravity erosion. Rill erosion and shallow landslide erosion exhibited the highest frequency of occurrence on the new and old terraces, respectively. The erosion moduli of the gully, scour hole, and sink hole on the new terraces were 171.0%, 119.5%, and 308.7% greater than those on the old terraces, respectively. In contrast, lower moduli of collapse and landslide were observed on the new terraces in comparison to the old terraces, reflecting reductions of 34.2% and 23.4%, respectively. Furthermore, the modulus of water erosion (32,102 t/km²) was 4.5 times that of gravity erosion on the new terraces. Conversely, on the old terrace, the modulus of gravity erosion (8804.1 t/km²) exceeded that of water erosion by 14.5%. Gully erosion and collapse dominated the erosion processes, contributing 67.8% and 9.4% to soil erosion on the new terraces and 38.7% and 34.0%, respectively, on the old terraces. In the study area, the new terraces experienced significantly greater erosion (39,252 t/km²) compared to the old terraces (16,491 t/km²). Plastic film mulching, loose and bare ridges and walls, inclined terrace platforms, and high terrace walls, as well as the developing flow paths, might be the key factors promoting the severe erosion of the terraces during heavy rainfall. Improvements in terrace design, construction technologies, temporary protective measures, agricultural techniques, and management strategies could enhance the prevention of soil erosion on terraces during heavy rainfall events. Full article

Accurately monitoring the morphology and spatiotemporal evolution characteristics of the entire process of slope erosion rill development is essential to circumvent the limitations inherent in traditional methods that rely on average flow velocity for hydrodynamic parameter calculations. This study employs an environmental chamber and a self-developed slope erosion test device to perform erosion tests on slopes with varying gradients and rainfall intensities. By integrating the structure-from-motion (SfM) method, fixed grid coordinate method, and continuous camera combined with the dye tracer technique, the morphological indexes and hydrodynamic parameters of the entire rill development process are precisely computed. The main conclusions are as follows: The entire process of slope rill development can be divided into three distinct stages. The initial stage is characterized by the appearance of tiny rills with mild erosion. The middle stage involves severe transverse spreading erosion and longitudinal undercutting, resulting in diverse rill morphologies. The final stage is marked by the stabilization of morphological characteristics. The peak slope soil loss is observed during the middle stage of rill development. The most effective parameters for characterizing slope soil loss from the beginning to the end are the Reynolds number and flow shear stress, the Froude number and flow shear stress, and the Froude number during different periods. Throughout the development of rills, the flow velocity initially decreases and then gradually increases until it stabilizes. The morphological indexes, including rill density, dissected degree, inclination, and complexity, generally show an increasing trend. However, in the middle stage, the rate of increase slows down, followed by a sharp rise at certain points. The optimal hydraulic parameters for evaluating rill density across different slope gradients, which were found to be the Darcy–Weisbach drag coefficient and real-time flow velocity, for assessing rill dissected degree, complexity, and inclination, were the Reynolds number and flow power. Under varying rainfall intensities, the most effective hydraulic and kinetic parameters for evaluating rill density, dissected degree, and inclination were flow shear stress and Reynolds number; for assessing rill complexity, the Reynolds number and flow power were used. The findings of this research enhance the accuracy of hydrodynamic parameter calculations in rill erosion tests, enable precise prediction of rill development trends on slopes, and offer innovative approaches for real-time dynamic monitoring of rill morphology and characteristics. These advancements are of significant importance for soil and water conservation and sustainability. Full article

Accurately characterizing rainfall runoff processes in plain farmland, especially at the plot scale with significant micro-topographic features, has presented challenges. Integrated surface–subsurface flow models with high-precision surface flow modules are appropriate tools, yet open-source versions are rare. To address this gap, we proposed an open-source integrated surface–subsurface flow model called the FullSWOF-Plain model, in which the one-dimensional subsurface module Hydrus-1D was integrated with a modified two-dimensional surface water flow module (FullSWOF-2D) using the sequential head method. Various experimental scenarios were simulated to validate the model’s performance, including two outflow cases (i.e., 1D and 2D) without infiltration, a classical one-dimensional infiltration case, and two typical rainfall events at the experimental field. The results demonstrate the accuracy of this proposed model, with the Nash–Sutcliffe efficiency (NSE) of the simulated discharge exceeding 0.90 in the experimental field case and the root mean squared error (RMSE) values for soil moisture at five depths consistently below 0.03 cm³/cm³. However, we observed a lag in the simulated response time of soil moisture due to the neglect of preferential flow. The micro-topography significantly influenced ponding time and ponding areas. Lower local terrain normally experienced earlier surface ponding. Scattered surface ponding water first occurred in the ditch and followed in the relatively low areas in the main field. The concentration process of surface runoff exhibited hierarchical characteristics, with the drainage ditch contributing the most discharge initially, followed by the connection of scattered puddles in the main field, draining excess surface water to the ditch through rills. This quantitative study sheds light on the impact of micro-topography on surface runoff in plain farmland areas. Full article