Soil Erosion Model Research Articles

Крупномасштабное моделирование эрозионных потерь почвы на основе уравнения RUSLE и разновременных данных дистанционного зондирования в условиях лесостепной зоны Среднего Предуралья

The article presents the results of modeling soil erosion losses based on the RUSLE equation using multi-temporal remote sensing data, which were used to determine the factor of complex characteristic of the influence of the farming system on soil erosion. The purpose of the research is to assess the significance of taking into account the crop rotation factor established on the basis of the seasonal dynamics of NDVI. The territory of the Arbashevsky rural settlement was chosen as the object of research in the forest-steppe zone of the Republic of Bashkortostan. An array of 16 fields containing a significant proportion of slightly and moderately eroded gray forest soils in the structure of the soil cover was analyzed. The proposed approach combines an expert assessment of NDVI graphs with reference data on erosion hazard coefficients for various types of land. The technique allows you to correctly identify the types of land and take into account their impact on erosion processes. The effectiveness of this approach is demonstrated using the example of agrolandscapes of the forest-steppe zone of the Republic of Bashkortostan. The results obtained reflect an increase in the accuracy of the forecast of erosion losses of soil by 78%. Keywords: NDVI, RUSLE, SOIL EROSION

Investigating soil erosion vulnerable zones based on clustered geoinformatics approach: a case study of Tyume River Catchment, Eastern Cape, South Africa

Rigorous field surveys, environmental specificity, and data paucity hamper detailed soil erosion assessments, model selection, ecological monitoring, and prioritization against soil erosion. To address this in a topographically complex environment, the present study presents a novel selection of physiographic factors integrated geospatially with the land use/cover and geology data to prioritize the soil erosion vulnerable areas within a watershed, using Tyume River Catchment, Eastern Cape, South Africa as a case study. A quantitative morphometric analysis involving parameters such as the drainage density, topographic wetness index, terrain ruggedness index, topographic position index, and vector roughness measure was computed using a digital elevation model based on their inference of watershed's morphogenetic response to anthropic factors and pluviometric processes. Based on expert judgment for thematic ranking and weightage, the soil erosion prioritization area map was generated through weighted overlay analysis of the morphometric parameters with land use land cover and surficial lithology themes. The results depicted a catchment-scale soil erosion vulnerability map, classified into very high (40 km2), high (135 km2), medium (209 km2), low (186 km2), and non-vulnerable (113 km2) zones. Using Google Earth image analyses through the coefficient of determination (R2 = 0.563) and Receiver Operating Characteristics Curve (AUC = 0.899), the model corroboration indicated that the soil erosion vulnerability assessment is reliable and highly predictive. The study identified free-range animal operation and hillslope overgrazing, especially in riparian zones, as the environmental practices aggravate the catchment's terrain susceptibility to soil erosion. The assessment showed that some of the selected morphometric parameters could be used to improve the validated soil erosion models in mountainous regions. Due to the high precision of the engaged approach and the identified environmental concerns, the method can be adopted in similar environments.

Coupling Benefit of Land Use, Land Cover Change and Soil Erosion Under Algorithmic Optimization Model

Technology realizes the quantitative and positioning acquisition of soil erosion and land use information, grasps the relationship between the two from space, and provides theoretical reference and scientific basis for local ecological environment construction and soil and water conservation work. This paper uses remote sensing images in my country in 2020 and 2021 as the data source and obtains land use data in four periods respectively. The experimental results show that the land use structure in my country has undergone great changes in 2020, and the land use type has gradually changed from a structure dominated by cultivated land, grassland, and unused land to grassland, forest land, and cultivated land. The other four types of land use area have increased to varying degrees, the unused land has decreased significantly, and the grassland and forest land have increased significantly; there are differences in the changes in the degree of land use in each study period, and the overall level of land use has developed phase by phase toward higher levels. In addition, this paper also studies the clustering algorithm in machine learning and proposes an improved interpolation algorithm for the completion of the original rainfall data. This algorithm can also be applied to the calculation process of rainfall erosion factors, which realizes the automatic calculation system of soil erosion model factors, realizes the real-time calculation and monitoring of soil erosion in the form of calculation tasks, and solves the problem that manual calculation consumes manpower and material resources.

Validation of Soil Detachment Rate Equations on Spring Thaw Period Slopes: Insights From Sediment Concentration and Transport Capacity

AbstractSoil detachment plays a central role in the formulation of soil erosion models, particularly for the simulation and prediction of erosion in cold climates during the thaw period. This research attempts to elucidate the mechanisms of soil detachment on spring thaw period slopes through comprehensive flume experiments, coupled with the application of rare earth element (REE) tracer, investigating the relationships between soil detachment rates, sediment concentration and sediment transport capacity. Observations indicate a nuanced response of soil detachment rate and sediment concentration to scour duration, characterized by an initial increase, subsequent decrease and eventual equilibrium. As thaw depth increases, the primary source of eroded sediment gradually shifts from the upper slope to the mid‐slope. Soil detachment rate was affected by sediment concentration, flow discharge, slope gradient, thawing depth, and slope positions. Furthermore, our analysis reveals a power function relationship (R2 = 0.846) between soil detachment rate, effective shear stress, and sediment transport rate and capacity. These results provide valuable insights into the modeling and prediction of soil erosion processes on brown soil slopes subjected to spring thaw period cycles.

A Geographic Information System (GIS) based Soil Erosion Model for Estimation of Sediment Yield for Kshipra River Basin, Madhya Pradesh India

A Geographic Information System (GIS) based Soil Erosion Model for Estimation of Sediment Yield for Kshipra River Basin, Madhya Pradesh India

Comparative effects of intermittent and continuous simulated rainstorms on rill erosion based on photogrammetry

AbstractDespite artificial rainfall simulation proves invaluable for the study of soil erosion processes and model construction, it still fails to fully replicate the characteristics of natural rainfall. Currently, most artificial rainfall experiments have carried out a large number of continuous high‐intensity rainfall due to the focus on the characteristics of short duration and high intensity of natural rainstorm but have ignored the erosion effects caused by intermittent rainstorm with low intensity and long duration. In this study, two sets of artificial rainfall simulation experiments of intermittent low‐intensity rainstorm (RR1) and continuous high‐intensity rainstorm (RR2) were conducted to evaluate the effects of rainfall characteristics on erosion morphology, runoff generation and soil loss. The evolution morphology monitored by a digital close‐range photogrammetry technology demonstrated the difference between the two rainstorm regimes. The soil surface was damaged more seriously under rainfall of RR2, and the rill morphological indicators of RR1 were all less than that of RR2. As rainfall proceeded, morphological indicators except for rill width‐depth ratio gradually increased. As a result, the runoff rate and sediment yield between two regimes were distinct. The segmented and total soil loss, average runoff rate and sediment concentration of RR1 were all less than that of RR2, with the total soil loss of the two rainstorm regimes being 275 and 683 kg, respectively. Water infiltration, rainfall intensity, duration and frequency may be the main factors leading to the difference in soil loss and erosion morphology between two rainstorm regimes. The inconsistency of these factors can easily cause the deviation of understanding of soil erosion mechanism. Therefore, the comparison of erosion effects under different rainstorm regimes has important implications for the improvement of natural rainstorm simulation and the comprehensive understanding of erosion mechanism.

Evaluation of the applicability of three sediment transport capacity equations on steep colluvial slopes and their modifications

AbstractAccurate estimations of the sediment transport capacity (Tc) are essential for soil erosion modelling. However, the applicability of existing Tc equations to colluvial soils with high steep slopes and high gravel content is limited. In this study, the variation of Tc with shear stress (τ), unit stream power (P) and stream power (ω) is investigated for different slopes and flow discharge. We also evaluate the applicability of the Yalin, Govers and GUEST equations (based on τ, P and ω, respectively) for estimating Tc on steep–slope colluvial deposits. Experiments were conducted using colluvial soil in a non‐erodible rill flume. The results reveal that Tc follows a power function with τ and ω and a linear function with P. The regression results of the three hydrodynamic parameters and Tc agree with the Tc equation forms of the corresponding equations. The Yalin equation, developed based on gently sloping erodible bed conditions, simulates overall low Tc values for steep sloping non‐erodible bed conditions (P.O.0.5–2 = 42.8%). The accuracy is significantly improved by correcting the sediment transport coefficient Kt (P.O.0.5–2 = 100%). The accuracy of the Govers‐simulated Tc values under steep slope conditions, based on gentle slope conditions, decreases with increasing slope gradient (P.O.0.5–2 = 37.14%), which is attributed to the large amount of coarse‐grained sediment present in this study. Thus, we retained the original form of the equation and further improved its accuracy by adjusting the coefficients (P.O.0.5–2 = 94.29%). As Tc increases, the GUEST equation can accurately simulate Tc. The accuracy is improved by calibrating the F‐value (P.O.0.5–2 = 100%). Using dimensional analysis, the equations built based on hydraulic conditions (excess current power, shear stress, flow velocity, etc.) and median particle size can accurately simulate Tc values (P.O.0.5–2 = 100%). These findings provide a basis for the development of erosion models for avalanche deposits on steep slopes.

Estimation of Crop Residue Cover Utilizing Multiple Ground Truth Survey Techniques and Multi-Satellite Regression Models

Soil erosion within agricultural landscapes has significant environmental and economic impacts and is strongly driven by reduced residue cover in agricultural fields. Large-area soil erosion models such as the Daily Erosion Project are important tools for understanding the patterns of soil erosion, but they rely on the accurate estimation of crop residue cover over large regions to infer the tillage practices, an erosion model input. Remote sensing analyses are becoming accepted as a reliable way to estimate crop residue cover, but most use localized training datasets that may not scale well outside small study areas. An alternative source of training data may be commonly conducted tillage surveys that capture information via rapid “windshield” surveys. In this study, we utilized the Google Earth Engine to assess the utility of three crop residue survey types (windshield tillage surveys, windshield binned residue surveys, and photo analysis surveys) and one synthetic survey (retroactively binned photo analysis data) as sources of training data for crop residue cover regressions. We found that neither windshield-based survey method was able to produce reliable regressions but that they can produce reasonable distinctions between low-residue and high-residue fields. On the other hand, both photo analysis and retroactively binned photo analysis survey data were able to produce reliable regressions with r2 values of 0.57 and 0.56, respectively. Overall, this study demonstrates that photo analysis surveys are the most reliable dataset to use when creating crop residue cover models, but we also acknowledge that these surveys are expensive to conduct and suggest some ways these surveys could be made more efficient in the future.

Spatiotemporal Variability of Soil Erosion in the Pisha Sandstone Region: Influences of Precipitation and Vegetation

The Pisha sandstone area, situated in the upper and middle reaches of the Yellow River in China, is characterized by severe soil and water erosion, making it one of the most critical regions on the Loess Plateau. The rugged terrain and exposed bedrock complicate management efforts for this area, posing challenges for accurate forecasting using soil erosion models. Through an analysis of terrain, vegetation, and precipitation impacts on soil erosion, this study offers theoretical support for predicting soil erosion within the exposed Pisha sandstone area of the Loess Plateau. This has substantial implications for guiding water and soil conservation measures in this region. Focusing on China’s exposed sandstone area within the Geqiugou watershed, temporal and spatial changes in vegetation cover and land use from 1990 to 2020 were analyzed. The result shows that, from 1990 to 2020, the grassland area has exhibited a consistent downward trend, with successive reductions of 64.86% to 59.46%. The area of low vegetation cover witnessed a significant decline of 59.29% in 2020 compared to that in 1990. The moderate erosion area decreased from 84.52 to 57.17 km2. The significant reduction in soil and water loss can be attributed to the expansion of forest and grassland areas, with the implementation of the Grain for Green project serving as a key policy driver for facilitating this expansion. This study provided a good example of combining rainfall with vegetation coverage to fast estimation soil erosion. A mathematical relationship between the vegetation rainfall coupling index (RV) and soil erosion was established with strong fitting effects, enabling estimation of the soil erosion volume under varying slope conditions within Pisha sandstone areas. The main focus of future soil and water conservation in the Pisha sandstone area should be on effectively managing the channel slope and minimizing exposed bedrock areas through a combination of slope cutting, the application of anticorrosive materials, and the implementation of artificial vegetation planting.

An Evaluation of the Sediment Reduction Benefits of Soil and Water Conservation Measures under Extreme Rainfall Conditions in the Loess Plateau in China Based on a Distributed Soil Erosion Model

Since the 1970s, comprehensive control measures on soil erosion in the headwater region of the Loess Plateau have been carried out. Quantitative evaluation of the benefits of soil and water conservation measures during extreme rainstorms is of great significance for the comprehensive management of the catchments. In this study, a systematic modeling methodology for evaluating the effects of soil and water conservation measures on sediment reduction was developed based on a distributed soil erosion model (DSEM). Taking the Chabagou basin in the Loess Plateau as the study area, the tested DSEM was used to simulate soil erosion and sediment yield during an extreme rainstorm under two scenarios, the uncontrolled condition and the controlled condition with soil and water conservation measures implemented. The results showed that DSEM could successfully simulate soil and water losses and evaluate the effects of soil and water conservation measures during extreme storm events. The evaluated results showed that each soil and water conservation measure had the specific function of sediment reduction. And under rainstorm conditions, the effect of engineering measures on sediment reduction was greater than that of forest and grass measures.

The Application of Soil Erosion Models of an Agroforestry Basin under Mediterranean Conditions from a Geotechnical Point of View

Soil erosion has been causing an imbalance in nature and the environment. It is mainly caused naturally but is also due to human interventions leading to desertification and possible contamination. Therefore, engineering, geography, and cartography have been allies in applying erosion models to predict, address, and remediate the impacts. Therefore, the Revised Universal Soil Loss Equation (RUSLE) and Soil and Water Assessment Tool (SWAT) linked to Geographic Information Systems (GISs) could boost decision making as tools to mitigate issues. This study applies the RUSLE and SWAT models from a geotechnical point of view to analyze a sub-watershed at Idanha-a-Nova (Portugal) over 4 years, showing a predominant erosion risk class with losses lower than 5 t.ha−1.year−1 (60 to 86%), characterized as very low risk. The modeling permitted the development of soils erosion susceptibility charts, in addition to material availability and the suitability for construction areas, exposing a replicable methodology that could contribute to minimizing environmental impacts while encouraging a more intelligent use of the land towards a greener exploration.

Modeling of soil erosion based on geospatial techniques and the RUSLE model for the Ugam Chatkal National Park, Uzbekistan

Soil erosion significantly impacts agriculture and the environment, posing threats to food security, economic stability, and social development . Today, modern technologies are effectively used by world scientists to assess soil erosion and take measures against it. This study leverages modern technological advancements for the evaluation and management of soil erosion, specifically within the Ugam Chatkal National Park in Tashkent region. This research employed Geographic Information Systems (GIS) and the Revised Universal Soil Loss Equation (RUSLE) model to assess erosion processes and quantify annual soil loss in the park. Thematic layers (R,P,C,K,LS) for this model were created using GIS. In this way, the impact of each factor on soil erosion can be seen more clearly. According to the obtained results, it was found that the R and LS factors have a greater effect on soil erosion than the other factors. Findings indicate a heightened susceptibility of the Ugam Chatkal National Park to water erosion. The estimated average annual soil erosion rate ranges between 0.00 and 250 tons per hectare per year (t ha-1 yr-1). The results underscore the need for developing and implementing strategic measures to prevent water erosion in the park and to mitigate its impacts. The study emphasizes the importance of current technologies in recognizing and addressing environmental issues, particularly soil erosion, which has far-reaching implications for ecological preservation and sustainable development. This study not only sheds light on the erosion dynamics of the Ugam Chatkal National Park, but it also stresses the critical importance of taking proactive actions to protect the park’s ecological integrity. Failure to treat erosion in time could result in lasting damage to the park’s rich biodiversity and scenic vistas. The integration of modern technologies such as GIS and the RUSLE model not only enhances our understanding of soil erosion processes but also empowers conservation efforts, offering a promising pathway towards ensuring the long-term sustainability of natural ecosystems.

Sediment Transport Dynamics Modeling of Overland Flow on Gentle Slopes Based on Flume Experiments

ABSTRACTSoil erosion is a global environmental issue, and sediment transport capacity (T c ) is critical for developing soil erosion models. This study conducted flume drainage experiments at six flow discharges (0.15, 0.25, 0.35, 0.45, 0.55, and 0.65 L s−1) and eight slope gradients (1.5, 3.0, 4.5, 6.0, 7.5, 9.0, 10.5, and 12.0°) to investigate how the T c of gentle slopes in the northeastern hilly region of China and water erosion factors are related and to establish a T c model of overland flow. The study demonstrated a power–law relationship between T c, flow discharge, and slope gradient, as evidenced by a high coefficient of determination (R 2; 0.94) and Nash–Sutcliffe efficiency (NSE; 0.92) values. Additionally, there was a positive correlation between T c and average flow velocity, with R 2 and NSE values of 0.86 and 0.84, respectively. Among the hydrodynamic parameters tested, the average flow velocity was determined to be the most effective T c predictor, surpassing stream power (R 2 > 0.7, NSE > 0.7), shear stress (R 2 > 0.6, NSE > 0.6), and unit stream power (R 2 < 0.5, NSE < 0.5). These findings lay the foundation for developing process‐based sediment transport models for gentle slopes in the northeastern hilly regions of China.

From Field to Model: Determining EROSION 3D Model Parameters for the Emerging Biomass Plant Silphium perfoliatum L. to Predict Effects on Water Erosion Processes

The agricultural production of maize (Zea mays L.) increases the risk of water erosion. Perennial crops like cup plant (Silphium perfoliatum L.) offer a sustainable alternative to produce biomass for biogas plants. The assessment of soil conservation measures requires calibrated soil erosion models that spatially identify soil erosion processes. These support decision-making by farmers and policymakers. Input parameters for the physically based soil erosion model EROSION 3D for cup plant cultivation were established in a field study. Rainfall simulation experiments were conducted to determine the model input parameter’s skinfactor and surface roughness. The results showed a reduction of soil erosion and higher infiltration rates for cup plant resulting in higher skinfactors of 11.5 in June and 0.75 post-harvest (cup plant) compared to 1.2 in June and 0.21 post-harvest (maize). With the extended parameter catalogue of EROSION 3D for cup plant cultivation model simulations were conducted for a rainfall event in June (64 mm). The sediment budget would have been reduced by 92.6% through the growth of cup plant in comparison to conventionally grown maize. Perennial cup plant can, therefore, contribute to achieving the targets outlined in the European Green Deal by reducing soil erosion and enhancing soil health.

Simulation and Spatio-Temporal Analysis of Soil Erosion in the Source Region of the Yellow River Using Machine Learning Method

The source region of the Yellow River (SRYR), known as the “Chinese Water Tower”, is currently grappling with severe soil erosion, which jeopardizes the sustainability of its alpine grasslands. Large-scale soil erosion monitoring poses a significant challenge, complicating global efforts to study soil erosion and land cover changes. Moreover, conventional methods for assessing soil erosion do not adequately address the variety of erosion types present in the SRYR. Given these challenges, the objectives of this study were to develop a suitable assessment and prediction model for soil erosion tailored to the SRYR’s needs. By leveraging soil erosion data measured by 137Cs from 521 locations and employing the random forest (RF) algorithm, a new soil erosion model was formulated. Key findings include that: (1) The RF soil erosion model significantly outperformed the revised universal soil loss equation (RUSLE) model and revised wind erosion equation (RWEQ) model, achieving an R2 of 0.52 and an RMSE of 5.88. (2) The RF model indicated that from 2001 to 2020, the SRYR experienced an average annual soil erosion modulus (SEM) of 19.32 t·ha−1·y−1 with an annual total erosion in the SRYR of 225.18 × 106 t·y−1. Spatial analysis revealed that 78.64% of the region suffered low erosion, with erosion intensity declining from northwest to southeast. (3) The annual SEM in the SRYR demonstrated a downward trend from 2001 to 2020, with 83.43% of the study area showing improvement. Based on these findings, measures for soil erosion prevention and control in the SRYR were proposed. Future studies should refine the temporal analysis to better understand the influence of extreme climate events on soil erosion, while leveraging high-resolution data to enhance model accuracy. Insights into the drivers of soil erosion in the SRYR will support more effective policy development.

Coupling Soil Erosion and Sediment Transport Processes With the Variable Infiltration Capacity Model (VIC‐SED) for Applications Suitable With Coarse Spatial and Temporal Resolutions

AbstractUnderstanding soil erosion and sediment transport from the hillslope scale to the regional scale is crucial for studies on water quality, soil‐water conservation, the lateral carbon cycle, environmental zoning and vulnerability. However, most existing erosion and sediment transport models are only applicable at the hillslope scale or for small watersheds with fine spatial resolutions (typically much less than 1 km). This study presents a process‐based soil erosion and sediment transport model for model applications designed for applications with coarse spatial (e.g., ≥10 km) and temporal (e.g., from hourly to daily) resolutions. This new model, referred to as VIC‐SED, effectively accounts for interactions between erosion and hydrological processes. This is achieved by tightly coupling the erosion processes with a hydrologically based Three‐layer Variable Infiltration Capacity (VIC‐3L) land surface model (LSM) and to a multi‐scale routing (MSR) model. VIC‐SED considers the impacts of (a) the spatio‐temporal variability of rainfall intensity on erosion processes and (b) soil moisture on the soil detachment process. VIC‐SED is evaluated in two watersheds. Results demonstrate that VIC‐SED is capable of reproducing water and suspended sediment discharges at coarse spatial resolutions and varying temporal scales varying from 15‐min to daily intervals. Our study indicates that the VIC‐SED model is a promising tool for studying and assessing the impacts of climate and land cover changes on suspended sediment yields over large regions using coarse spatial and temporal resolutions.

Integrated Modeling of Flow, Soil Erosion, and Nutrient Dynamics in a Regional Watershed: Assessing Natural and Human‐Induced Impacts

AbstractCurrent integrated modeling frameworks for simulating nutrient sources and dynamics are inadequate for large regional watersheds dominated by groundwater‐surface water interactions due to their simplistic representations of groundwater. In this study, we develop a coupled model that integrates comprehensive surface water, 3‐D groundwater, soil erosion, and nutrient processes. The model is intended to enhance the understanding of nutrient dynamics and sources in the Pearl River Basin (PRB). The model exhibits satisfactory performance in simulating streamflow and sediment transport patterns, capturing essential seasonal variations in water quality indicators. Hydrological budget assessments from 2002 to 2020 in the PRB reveal that 54% of precipitation drains into the South China Sea as surface water, while groundwater discharge as baseflow accounts for 18% of the streamflow. The nutrient budget for the PRB indicates that non‐point sources are the dominant contributors to both nitrogen (N) and phosphorus (P), ranging between 64% and 90%. Improved sewage collection and treatment have reduced point source nutrient contributions over the evaluation period. Groundwater remains a significant and consistent source of N, contributing between 11% and 19%. Natural disturbances and fertilization have led to an upward trend in river N inputs, while afforestation and sewage reduction efforts have resulted in a downward trend in river P inputs. Increased fertilization emerges as a central concern for the PRB, suggesting cost‐effective mitigation of fertilizer usage a pragmatic solution. The coupled simulation model developed in this study offers a novel systems approach for basin‐wide nutrient analysis and pollution control strategies, considering both natural and human‐induced disturbances.

Empirical and physical modelling of soil erosion in agricultural hillslopes

Abstract Soil erosion is a complex and highly heterogeneous process with a wide range of environmental and economic impacts. Its estimation is particularly challenging and modelling is typically used for erosion estimation over large areas. The aim of this study was to compare the two leading empirical and physical erosion estimation models, i.e. the Revised Universal Soil Loss Equation (RUSLE) and the Water Erosion Prediction Project (WEPP). The models were calibrated and validated using data collected from field experiments conducted in agricultural lands of Mexico. The simulated rainfall experiments involved measuring erosion from field plots subjected to four tillage systems (No crop, Conventional tillage, Conventional tillage + residues, and Handspike) under two antecedent soil moisture conditions (dry and wet). Different calibration approaches based on the factors K and C for RUSLE, and interrill erodibility and hydraulic conductivity in WEPP were tested. The best-performing methods in RUSLE involved measuring the K factor and adopting the recommended C factor by the National Forestry Commission of Mexico. In WEPP, the best results were obtained when interrill erodibility was estimated from experimental measurements. Overall, RUSLE outperformed WEPP in most of the treatments except for CT under WAMC.

Microtopographic response of tilled loess slopes during stages of water erosion development

The tilled slopes in the loess region are characterized by artificial management practices that result in variations in microtopography, which serve as both the site of water erosion and a significant factor contributing to further slope erosion development. However, the response of microtopography during the process of erosion development on tilled loess slopes is unclear. In this study, artificial rainfall simulations were conducted to simulate the development of water erosion (splash erosion (SpE), sheet erosion (ShE), and rill erosion (RE)) under three slope gradients (5°, 10°, and 20°) and three tillage practices (artificial backhoe (AB), artificial digging (AD), and contour tillage (CT)) at a rainfall intensity of 60 mm h−1. The spatial correlation and heterogeneity of the microtopography were analysed using semivariogram functions and fractal dimensions. The response characteristics of microtopography during the water erosion development process on tilled loess slopes were analysed from three perspectives: microtopography factors, erosion equilibrium areas, and slope strips M-ΔDEM. The results indicated that the microtopography process data exhibited moderate to high spatial autocorrelation. There is a positive correlation between microtopographic factors and the slope gradient. Tilled slopes exhibit erosion equilibrium effects during the processes of splash erosion, sheet erosion, and rill erosion. These equilibrium effects are located in the longitudinal ranges of 700 to 1200 mm, 700 to 1300 mm, and 800 to 1100 mm, respectively. Soil erosion and deposition primarily occur in the middle and lower parts of the slope, with 70 % of the slope’s elevation changing within 10 mm, while the remaining changes can reach 25 mm. Among the three tillage practices, AB is the most susceptible to slope influences, which can lead to soil loss, and an optimal slope gradient exists for implementing AB measures. In the case of CT at a slope of 20°, ridge breaking is more likely to occur, but considering the combined effects of soil loss suppression and the difficulty in forming rills, it is recommended to prioritize CT as the preferred tillage practice among the three practices. This study can provide a theoretical foundation for understanding the mechanisms through which microtopography influences water erosion. Additionally, it can serve as a theoretical basis for calibrating parameters in soil erosion models for sloping cultivated lands.

A thermal infrared imaging observation system for the measurement of overland flow velocities under controlled laboratory conditions

Flow velocity is an important physical parameter in characterizing the hydraulics of water flow. The accurate measurement of overland flow velocities has great significance for understanding and modeling sediment transport and soil erosion. In this study, a Thermal Infrared Imaging Observation System (TIIOS) based on thermal infrared imaging techniques and computer vision recognition technology was established to measure overland flow velocities under controlled laboratory conditions. TIIOS has three subsystems including thermal tracer control, image acquisition and transmission, and image storage and processing. It can be used to dynamically monitor changes in shallow flow velocity by means of automatic control of thermal tracer, instantaneous image acquisition, image correction, noise removal and centroid determination. The observation precision was high with a standard deviation of 0.004 m·s−1 for flow velocity, a temporal resolution of 1/9th s, and a spatial resolution of 2 mm. The new system achieved higher accuracy compared to the traditional dye tracing and salt tracing techniques in observing the dynamic transport process of thermal tracer movement. The relative errors of the centroid velocity measured by the TIIOS ranged from −9.83 % to 6.40 %; whereas the relative errors of centroid velocity measured by salt tracer ranged from −21.36 % to 17.22 %. Measurements by the established TIIOS under different hydraulic conditions demonstrate that the relative errors of the centroid velocity are all smaller than those of the leading-edge velocity. This observational system provided a reliable way to measure shallow flow velocity for better understanding the mechanisms of water erosion processes and showed its potential to be used in field experiments under natural conditions.