Erosion Control Measures Research Articles

Land-Use-Change-Driven Erosion and Sediment Transport in the Yaqui River Sub-Basin (Mexico): Insights from Satellite Imagery and Hydraulic Simulations

Soil erosion and sediment transport are significant concerns in the Yaqui River sub-basin in northwest Mexico, driven by land use changes and environmental degradation. This study aims to evaluate erosion processes between 2000 and 2020 using a combination of satellite imagery and numerical simulations with Iber software (Version 2.5.2). The primary objective is to assess the impacts of land use changes, particularly the conversion of forest to grassland, on erosion rates and sediment transport. Satellite images from 2000 and 2020 were analyzed to detect land cover changes, while Iber’s sediment transport module was used to simulate erosion patterns based on the Meyer–Peter and Müller equation for bedload transport. Hydrological and topographical data were incorporated to provide accurate simulations of flow velocity, depth, and erosion potential. The results reveal a 35.3% reduction in forest cover, leading to increased erosion and sediment transport in steep areas. Simulation predictions highlighted areas with high future erosion potential, which are at risk of further soil loss if current trends continue. Flow velocity increased, contributing to riverbank destabilization and higher sediment yield, posing a risk to infrastructure such as the Álvaro Obregón Dam. This study underscores the need for targeted erosion control measures and sustainable land management practices to mitigate future risks and protect vital infrastructure in the Yaqui River Basin.

Soil erodibility mapping using remote sensing and in situ soil data with random forest model in a mountainous catchment of Indian Himalayas.

Land degradation is accelerating in the Himalayan ecosystem, resulting in the loss of soil nutrients due to severe erosion. Soil erosion presents a significant environmental challenge, resulting in both on-site and off-site consequences, such as reduced soil productivity and siltation in reservoirs. Soil erodibility (K factor), an inherent soil property, determines the susceptibility of soils to erosion. Sampling across hilly and mountainous terrain pose challenges due to its complex landscape. Despite these challenges, it is essential to study K factor variations in different land use/land cover types to comprehend the threat of erosion. Digital soil mapping offers an opportunity to overcome this limitation by providing spatial predictions of soil properties. The objective of our study is to map the spatial distribution of soil erodibility using the Random Forest (RF) model, a machine learning method based on sampled in situ soil data and environmental covariates. We collected 556 surface soil samples from the mountainous catchment (Tehri dam catchment) using the stratified random sampling approach. The model performed satisfactorily in both training (r2 = 0.91; RMSE = 0.00185) and testing (r2 = 0.45; RMSE = 0.00318) phases. Subsequently, we generated a digital map with a resolution of 12.5m to depict the distribution of the K factor. Our analysis revealed that key environmental variables influencing the prediction of the K factor included geology, mean NDVI, and climatic factors. The average K factor value was estimated at 0.0304 and ranging from 0.0251 to 0.0400 t ha h ha-1MJ-1mm-1. A higher K factor was observed in the barren land (0.0344) primarily located in the higher and trans-Himalayan region of seasonally snow-covered areas. These areas typically feature young soils with weak soil formation and unstable soil aggregates. Subsequently cropland/cultivated soils (0.0307) exhibited higher K factor values due to the breakdown of soil aggregates by ploughing activities and exposing carbon to decomposition. The average K factor value of evergreen (0.0294) and deciduous (0.0295) forests were the lowest compared to other land use/land cover types indicating the role of forests in resisting soil erosion. By assessing and predicting soil erodibility, land planners and farmers can implement erosion control measures to protect soil health, prevent sedimentation in water bodies, and sustain agricultural productivity in the Himalayas.

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.

Spatial and Temporal Variability of Rainfall Erosivity in the Niyang River Basin

Rainfall erosivity is a crucial factor in the evaluation of soil erosion, significantly influencing the complex relationships among water, soil, and the environment. Understanding its attributes and variations in space and time is essential for effective water resource management, erosion mitigation, and land-use planning. This paper utilizes daily precipitation data from 123 grid points in the Niyang River Basin, spanning from 2008 to 2016, to calculate rainfall erosivity using a straightforward algorithmic model. Ordinary Kriging was used to examine the spatial and temporal variations in rainfall erosivity, while Spearman’s correlation analysis was employed to examine the relationships between annual rainfall erosivity and various factors, including multi-year average precipitation, erosive rainfall, dry-season rainfall, wet-season rainfall, temperature, and elevation. The results indicate a year-by-year increase in rainfall erosivity in the basin, with a trend towards stabilization. The average annual rainfall erosivity over the years is 711 MJ·mm·hm−2·h−1, peaking at 1098 MJ·mm·hm−2·h−1 in 2014. A significant 93.9% of rainfall erosivity is concentrated in the wet season, with a maximum of 191 MJ·mm·hm−2·h−1 in July. The left bank of the mainstream, especially the central and lower sections of the main river and its tributaries, experiences the highest rainfall erosivity. Rainfall factors predominantly influence erosivity, with erosive rainfall showing the strongest correlation (rho = 0.93), while temperature and elevation have relatively minor effects. This study enhances the understanding of rainfall erosive forces in the plateau region and provides a scientific basis for predicting soil loss, developing effective erosion control measures, and ensuring sustainable land use.

3D surface change detection of slope using 3D point cloud based on construction of double surface

Aiming at the complex geological conditions of slopes and the difficulty of manual investigation, this paper proposes a method of constructing double surface based on 3D point cloud data to estimate the depth of slope deformation and disaster analysis. Terrestrial Laser Scanner is utilized to collect the slope point cloud data. Through the construction of double surface to simulate the original slope, the deformation depth is estimated and the depth data are fused into the point cloud to realize the automatic identification of slope deformation disaster and the calculation of deformation depth, and provide the deformation depth map. The shortcomings of the traditional Multiscale Model and Model Point Cloud Comparison (M3C2) algorithm, which needs to capture multiple time periods of point cloud data for calculation can be overcome. And there is no need to recognize the segmentation of the slope point cloud. The study results show that the maximum relative error of slope deformation is 10.82% in slope deformation. The proposed method is suitable for detecting slope hazards in various scenarios, providing a basis for further analysis and the development of effective erosion control measures. It introduces a new technology for daily monitoring of slope deformations and can be extended to drone-based LiDAR applications.

Spatial analysis and assessment of soil erosion in the southern Western Ghats region in India.

Soil erosion is expected to worsen in the future as a result of climate change, growing population demands, improper land use, and excessive exploitation of natural resources in India. Due to the growing population and changes in land use, it has become increasingly crucial to map and quantitatively assess soil for the purpose of sustainable agricultural usage and planning conservation efforts. The problem of soil erosion is mainly on steeper slopes with intense rainfall in parts of Western Ghats. The 20.17% of geographical area have been converted into wasteland due to soil erosion. The Revised Universal Soil Loss Equation (RUSLE) is a highly prevalent and effective technique utilized for estimating soil loss in order to facilitate the planning of erosion control measures. Despite the fact that RUSLE is accurately estimate sediment yields from gully erosion, it is an effective tool in estimating sheet and rill erosions losses from diverse land uses like agricultural to construction sites. The current study is mainly about combining the RUSLE model with GIS (Geographic Information System) to find out how much soil is being lost, particularly in Noyyal and Sanganur watersheds which is located in Coimbatore district of Tamil Nadu, India. This analysis is based on the soil order, with a significant proportion of alfisols and inceptisols being considered. The obtained outcome is contrasted with the established soil loss tolerance threshold, leading to the identification of the areas with the highest susceptibility to erosion. Within the narrower and more inclined section of the watershed, yearly soil loss scales from 0 to 5455 tonnes/ha/year, with an average annual loss of soil of 2.44 tonnes/ha. The severe soil erosion of 100 to 5455 tonnes/ha/year is found along the steep and greater slope length. The generated soil map was classified into six categories: very slight, slight, moderate, high, severe, and very severe. These classifications, respectively, occupied 6.23%, 14.88%, 10.56%, 15.70%, 7.73%, and 6.63% of the basin area. Based on the results of cross-validation, the estimated result of the present study was found to be very high compared to past studies conducted 0 to 368.12 tonnes/ha/year especially in very severe erosion zones. But very slight to severe erosion zones nearly matched with same level of soil loss. To protect the soil in the study area from erosion, more specific actions should be taken. These include micro-catchment, broad bed furrows, up-and-down farming, soil amendment with coconut coir pith composition, streambank stabilization with vegetation, and micro-water harvesting with abandoned well recharge. These actions should be carried out over time to make sure to work.

Spatiotemporal analysis of sand and dust emission point sources detected from satellite imagery in Syria, Jordan, and Iraq

This study utilized MODIS true color satellite imagery to analyse blowing sand and dust events dynamics in the Middle East from 2010 to 2021, focusing on Syria, Iraq, and Jordan. A total of 4923 dust point sources were detected, with a significant concentration (~90 %) located within the Tigris-Euphrates Basin (Nearest Neighbor Ratio = 0.41, р < 0.001). Land cover analysis revealed that bare land, comprising most of the study area, was the predominant source of dust emissions. Wetlands, though only constituting about 1 % of the area, showed the highest frequency of dust sources per unit area, highlighting their role as critical dust emission hotspots. The study emphasizes the impact of drought and anthropogenic factors, such as poor land management, on blowing dust intensity. It suggests the necessity of strategic land management practices, including re-vegetation of arid areas, reducing soil exposure, and implementing wind erosion control measures. To effectively address the transboundary nature of dust emissions, the findings underscore the importance of fostering regional cooperation through mechanisms such as shared environmental monitoring and data exchange platforms, joint management of cross-border natural resources, and collaborative policy making.

Research on the economic loss prediction and vulnerability risk zoning of coastal erosion disaster: a case study from Liaoning, China

IntroductionCoastal erosion is widely distributed globally, with sandy coasts being particularly prominent, causing significant economic losses to coastal areas. This study focuses on the coastal areas of Liaoning Province, China, which represent typical sandy beach erosion.MethodsBased on the assessment of coastal erosion disaster losses, a multivariate variable-weight combination prediction model is utilized to predict the losses caused by coastal erosion disasters, providing an effective mathematical modeling approach for predicting such losses. Furthermore, the cluster analysis method is employed to delineate vulnerability risk zones for coastal erosion along the Liaoning Province coast.Results and discussionThe research findings indicate the following: (1) From 2023 to 2025, the losses due to coastal erosion disasters in Liaoning Province are projected to decrease significantly from a scale of 36 million RMB yuan to 5 million RMB yuan; (2) Based on the magnitude of disaster vulnerability risk, the coastal areas of Liaoning Province are categorized into four risk zones: high-risk zones (Jinzhou District), moderately high-risk zones (Zhuanghe City, Wafangdian City, Ganjingzi District), medium-risk zones (Lvshunkou District, Bayuquan), and low-risk zones (Gaizhou City, Suizhong County, Xingcheng City). Recommendations are proposed accordingly: (1) Effective measures should be implemented to mitigate the losses incurred by coastal erosion on land, buildings, infrastructure, agricultural output; (2) In the selection of disaster prevention and control measures,economic factors should be carefully considered in line with the specific circumstances of the losses. Specifically, the economic efficiency of disaster prevention and mitigation measures should be taken into account; (3) Precise efforts should be made to implement coastal erosion disaster prevention and control measures in different regions.

Spatial distribution of soil depth in relation to slope as a consequence of erosion-accumulation processes in loess lowland hills of Slovakia

Abstract In our study, we examined the influence of slope gradient on erosion processes and present soil formation and change on loess hills. We analysed data from the two study areas and found that slope gradient is a significant factor influencing soil depth as well as humus horizon thickness. At the Báb locality, we observed a negative correlation between slope gradient and soil depth (r = –0.206, p &lt; 0.05) and a negative correlation between slope gradient and humus horizon thickness (r = –0.227, p &lt; 0.01). At the Nová Vieska locality, there was a negative correlation between slope gradient and soil depth (r = –0.334, p &lt; 0.02), as well as between slope gradient and humus horizon thickness (r = –0.356, p &lt; 0.01). These findings confirm that slope gradient is a key factor influencing soil formation in loess hills, and has a significant impact on its depth and soil profile. The analysis revealed that a critical slope of 3° significantly influences soil formation, with shallower soils and a thinner humus horizon occurring on steeper slopes. Our findings have important implications for planning erosion control measures and soil management depending on the location and slope gradient. Overall, our work provides insights into soil formation processes in loess hills and contributes to a better understanding of the interactions between slope gradient and erosive processes.

Suitability of soil in Ukpiovwin community in Udu LGA of Delta state for oil palm plantation based on its physicochemical properties

Soils of Ukpiovwin community in Udu LGA of Delta State were evaluated for suitability for oil palm cultivation based on its physicochemical properties. Suitability of soils for oil palm was assessed using FAO’s land and soil requirement and suitability ratings. Soil texture classes identified were dominated by clay. The soils were slightly acidic, with pH ranged from 4.49 to 6.40. The results showed that certain land characteristics such as, mean annual temperature, rainfall, soil depth and drainage were rated highly suitable (S1) to marginal suitable (S2), organic matter, total nitrogen, and potassium were rated highly suitable (S1) Available phosphorus and ECEC were generally low and rated as marginally suitable (S3) for oil palm cultivation in the study area. The main limiting factors that lower the suitability of these soils for oil palm establishment in the area were the soil texture which is clay and the low level of phosphorus available the soil. In order to enhance the soil condition and raise the productivity of the land to an ideal level, focus should be put on soil management practices that will improve the soil’s ability to effectively drain water in order to prevent water logging and keep water at ≥20cm below soil surface. The amount of phosphorus available in the soil can be increased through the application of phosphate fertilizer and through installation of erosion control measures such as bunds, platforms, and terraces to lessen losses of native and applied phosphate in surface run-off water and eroded soil.

Holistic evaluation of inlet protection devices for sediment control on construction sites

To address the deleterious impacts of excess soil erosion from the construction sites, the United States Clean Water Act requires that erosion and sediment control measures (ESCs) be implemented on construction projects disturbing more than 0.4 ha. Inlet protection devices (IPDs) are a common ESC utilized on construction projects to reduce the amount of sediment entering storm sewers. In Ohio, regulatory agencies use approved, non-proprietary IPDs made from commonly available materials (e.g., silt fence, geotextile, lumber, and aggregate) to mitigate sediment on construction projects; however, these IPDs often rely on extended ponding to remove sediment and require frequent maintenance making these unsuitable for road construction projects. Commercially manufactured (i.e., proprietary) IPDs which rely on filtration to quickly dewater following rainfall may prove more practical for road construction projects. However, little research which quantitatively compares the holistic performance of these two types of IPDs in field settings has been performed to date. To address this knowledge gap, the performance of 24 proprietary IPDs was evaluated at field-scale using simulated construction site runoff and compared to three non-proprietary IPDs currently approved for use in Ohio. Bypass flows, which typically occurred due to poor IPD fit to standard drainage inlets used in Ohio transportation settings, significantly increased effluent total suspended solids (TSS) and turbidity compared to tests of IPDs where bypass did not occur. Overflow, or intentional bypass around primary IPD flow pathways during high flows, did not significantly impact effluent water quality. Despite differences in treatment mechanisms (i.e., sedimentation versus filtration), the water quality performance of non-proprietary and proprietary IPDs were not statistically different, indicating comparable sediment removal was provided by both categories. Findings from this research can provide design engineers and state regulatory agencies the necessary tools to evaluate IPD performance in road construction settings and, ultimately, alleviate the impact of excess sediment discharged from construction sites.

The impact of vegetation reconstruction on soil erosion in the Loess plateau

Vegetation restoration not only extensively reshapes spatial land use patterns but also profoundly affects the dynamics of runoff and sediment loss. However, the influence of vegetation restoration on runoff and sediment yield from a regional perspective are scarce. This study therefore focused on 85 sites within the “Grain for Green” Project (GGP) region on the Loess Plateau, to investigate the impacts of the GGP on soil erosion. The results revealed a notable reduction in sediment loss and runoff due to vegetation restoration. Since the inception of the GGP in 1999, approximately 4.1 × 106 ha of degraded lands have been converted into forestlands, shrublands, and grasslands, resulting in an average annual reduction of 1.4 × 109 m3 in runoff and a decrease of 3.6 × 108 t in annual sediment loss on the whole Loess Plateau, with the GGP contributing approximately 26.7% of the sediment reduction in the Yellow River basin. The reduced soil erosion has mainly been regulated by vegetation cover, soil properties (clay, silt, and sand), slope, and precipitation on the Loess Plateau. The insights gained offer valuable contributions to large-scale assessments of changes in soil erosion in response to vegetation reconstruction and enhance our understanding of the spatial configurations associated with soil erosion control measures.

Influence of Morphometric Relief Parameters on Soil Depth Changes and Humus Horizon Thickness in Relation to Erosion-Accumulation Processes: A Study in the Ipeľská Pahorkatina Hills, Slovakia

Abstract This study examines the spatial distribution of soil types and their susceptibility to erosion and accumulation processes in a study area in Slovakia. Field research involving 71 probes identified various soil types, with Regosols and Cutanic Luvisols being predominant. The study found that erosion-accumulation processes were detected in 69.97% of the probes, with changes observed in soil horizons. Soil analysis revealed different relations between soil depth, humus thickness, and terrain characteristics such as slope, slope length, and slope length and steepness factor (LS factor). Specifically, we confirmed a moderately strong positive correlation between soil depth and humus thickness (r = 0.597, n = 71, p &lt; 0.001). Shallow soils (0–30 cm) exhibited a very strong positive correlation between soil depth and humus horizon thickness (r = 0.978, n = 33, p &lt; 0.001). Conversely, no relationship was found in moderately deep soils (30–60 cm) (r = 0.018, n = 14, p &lt; 0.948). For deep soils, we identified a moderately strong positive correlation (r = 0.345, n = 24, p = 0.098). While slope and slope length showed relationships with soil depth and humus thickness, the LS factor did not exhibit a clear correlation. These findings underscore the importance of understanding soil dynamics in informing land management practices, especially in areas susceptible to erosion. Recommendations include continued monitoring of eroded soils and implementing erosion control measures to maintain soil health and sustainability in agricultural production amidst climate change challenges.

DESIGN OF ANTI-EROSION HYDRAULIC AND FORESTRY MEASURES TO COMBAT RAVINES

The article discusses the design of anti-erosion hydraulic and forestry measures to combat ravines in the territory of Kopenkuvate village, Golovanivsky district, Kirovohrad region. It has been established that climatic conditions (especially the distribution of precipitation, both in terms of the growing season and the intensity of precipitation) in some periods contribute to the acceleration of water erosion, especially gully erosion. According to hydrological calculations, the volume of runoff from the 10% snowmelt was 6792 m3, and the total solid runoff was 476 m3. An earthen rampart 186 m long and 2.0 m high was designed to capture the runoff. Reducing erosion intensity to acceptable levels is the main criterion for selecting erosion control measures. In addition to the agrotechnical erosion control measures used, the farm selected and designed their combination with hydrotechnical and forest reclamation measures that meet this condition. Simultaneously with the installation of the water retention berm, we create a forest strip along the ravine, which is placed on both sides of the ravine along its sides at a distance of 5 meters from them. The strip is 0.526 km long, 12.5 m wide, and has 5 rows. Amount of planting material: common oak - 1.052 thousand pieces; pear - 0.375 thousand pieces; white acacia - 0.375 thousand pieces; common dog rose - 0.750 thousand pieces; sea buckthorn - 1.052 thousand pieces. To strengthen the bottom of the ravine, we plan to install 15 wicker dams. The bottom of the ravine will be used for continuous forestation. To reforest the ravine bottom with an area of 0.52 hectares, we need 1,733 thousand poplar plants and 0.867 thousand rose hips. The complex of anti-erosion measures will reduce the intensity of erosion processes and the formation of ravines on agricultural lands.

Evaluation of the impact of erosion control measures on dam siltation and upstream erosion using radioisotope technique 7Be and MUSLE model in the watershed upstream of Allal El Fassi dam, Morocco

Water erosion poses a significant threat to the sustainability of natural resources and hydro-agricultural infrastructure, particularly in the Mediterranean region, including Morocco. The Allal El Fassi watershed faced such challenges and underwent anti-erosion measures between 2008 and 2014. This study aims to evaluate the effectiveness of these measures in mitigating dam siltation within the watershed. The methodologies employed include the utilization of the MUSLE model, optimized with bathymetric surveys of the dam, to estimate the amount of sediment reaching the dam and derive the P-factor associated with the implemented anti-erosion measures. Additionally, the radioisotope technique was utilized to assess erosion rates at managed and unmanaged sites within the watershed. The results obtained using the MUSLE model and bathymetric data revealed a noteworthy reduction in mean annual soil loss within the timeframe of 2002–2010 to 2010–2013, resulting in a 13.9% decrease in sediment reaching the dam. Furthermore, variations in the P-factor of erosion control measures were observed, ranging from 0.31 to 0.52 during the respective periods. Utilizing the radionuclide 7Be, erosion rates ranging from 6.8 to 25.3 t.ha−1 were determined for the studied plots, facilitating the calculation of P-factors for specific erosion control measures. Significantly, gabion check dams displayed a P-factor of 0.47, dry stone barriers had a P-factor of 0.41, fruit trees with basins showed a P-factor of 0.51, and enclosures exhibited a P-factor of 0.67. These findings suggest a causal relationship between the implementation of erosion control measures and the reduction in sedimentation rates at the Allal El Fassi Dam, highlighting the interdependence between the two phenomena.

A GIS‐based approach to site vegetated buffer strips for erosion control within an agricultural catchment in southern England

AbstractAgricultural soil erosion is largely attributed to arable intensification and increased mechanization. Runoff from arable land and intensively managed grassland transports sediment and contaminants across the landscape and into watercourses, causing crop loss, land degradation, and water quality issues. One low‐cost and low‐maintenance nature‐based mitigation approach is the implementation of vegetated buffer strips (VBS): grassland sited along field margins to trap sediment and contaminants, reducing transportation and diffuse pollution rates. GIS modelling using remotely sensed landscape indices and land parcel data can provide an efficient means of identifying priority areas for intervention at sub‐catchment or farm system scales. We develop and test a scalable runoff risk model in the lower Rother catchment, West Sussex. The model uses the Normalized Difference Vegetation Index (NDVI) applied to satellite images as an erodibility proxy and identifies locations along pathways that are conceivably at greatest risk of sediment accumulation and transfer, guided by field observations. We assess current and historical field boundaries near high‐risk locations, evaluating the potential capacity of their margins to contribute to runoff risk reduction using an innovative ranking system. Recommendations are made for VBS implementation and the value of historical field boundary and margin restoration is discussed. Our method offers a rapid approach with minimal data requirements to identify high‐risk sediment runoff locations and priority sites for intervention. The tool has the potential to guide decision‐makers responsible for targeting and implementing soil erosion and runoff control measures such as VBS, while also maximizing agri‐environmental and cultural benefits.

Sustainability concern in Indian agriculture: needs science-led innovation and structural reforms

Agriculture in India is facing several challenges which together are manifested into the sustainability issues. The broad contours of the agricultural production system in the country have been defined by the need to achieve food security which calls for close attention to rice–wheat (Triticum aestivum L.) cropping system of the Indo Gangetic Plains (IGP) whose sustainability is under threat. Degradation of natural resources, severe biotic and abi otic stresses specially drought, floods, pest infestations with accompanying impacts on biodiversity and agricultural productivity are the major constraints to agricultural development. Further, climate change has gained significant global attention over the past decade due to concerns of deleterious long-term impacts on agriculture, water sup ply, human welfare, regional and political stability. All the related issues need to be addressed on priority, with par ticular emphasis on soil-carbon through a holistic approach. As the strategy brings focus on income of farmers, the agricultural technology needs to move from “Production oriented-Green Revolution” to “Farmer’s Income oriented Revolution” and environmentally sustainable farming. Therefore, for long-term sustainability in agriculture, 4 pil lars/ components (good agricultural practices, climate-change mitigation and adaptation, diversification of high value crops and biodiversity management) needs to be addressed properly, more importantly good agricultural practices (GAP). The GAPs are based on the principles of risk prevention, risk analysis, sustainable agriculture, and integrated crop management (ICM), which are of utmost importance in present time. The GAPs for agricultural sustainability are reduced tillage, conservation agriculture, resource-conservation technologies (RCTs), erosion control measures, diversified cropping system, micro-irrigation, balanced fertilization, manuring, watershed man agement, organic farming, and integrated farming systems etc. Now that the vision is to impart income security to the farmers of the country, diversification of the system across all the sub-sectors of agriculture assumes impor tance which is, indeed a de-risking mechanism capable of negotiating both endogenous and exogenous risks as sociated with the system. The effective and efficient management of agro-biodiversity is also essential through management of genebanks, science-led innovations; livelihood, food and nutrition security though crop diversifica tion, use of lesser-known crops and wild relatives in crop improvement; dealing appropriately with quarantine, bio safety and bio-security.

Differences in sediment provenance from rainfall and snowmelt erosion in the Mollisol region of Northeast China

AbstractDifferences in erosion patterns inevitably lead to different soil loss processes. However, the differences in sediment sources between rainfall and snowmelt erosion are not well studied. To address this gap, a study was conducted in a small agricultural catchment (3.5 km2) using the fingerprinting technique to quantify the various sources contributing to sediment, as well as determine the magnitude of sediment total nitrogen (TN), total phosphorus (TP), total potassium (TK) and soil organic matter (SOM) loads from three sources (cultivated land, unpaved roads and gullies) during the rainy season and spring thawing period. Sediment sources from 17 rainfall erosion and seven snowmelt erosion events of varying magnitudes were compared. The Collins and Bayesian mixing models, coupled with geochemical tracers (Cs, V, Cd, Pb and Ag), were applied to assess the contribution proportion of individual sediment sources to suspended sediment. According to the results obtained from the Bayesian mixing model with higher accuracy, cultivated land, unpaved roads and gullies contributed 60.3% (load‐weighted mean contribution [LMC] = 82.8%), 11.0% (LMC = 6.5%) and 28.7% (LMC = 10.7%) of the sediment in the rainy season, respectively. Cultivated land was the dominant sediment source for rainfall erosion, with high rainfall erosivity and sediment concentration. However, for snowmelt erosion, gullies were the primary sediment source (LMC = 66.2%), followed by cultivated land (LMC = 19.8%) and unpaved roads (load‐weighted = 14.0%). Meanwhile, in the spring thawing period, the contributions of unpaved roads to sediment were higher than in the rainy season. During the rainy season, the greatest contributions of TN, TP, TK and SOM were observed from cultivated land, with respective LMC values of 94.2%, 89.4%, 81.1% and 94.8%. With the increase of sediment contribution from gullies in the spring thawing period, its LMC of TN, TP, TK and SOM increased to 42.6%, 58.3%, 65.0% and 38.0%, respectively. The results of the study could be useful for understanding the processes of soil erosion, clarifying the driving mechanism of compound erosion, developing the compound erosion prediction model and optimizing the spatial configuration of erosion control measures.

Monitoring the impacts of rainfall characteristics on sediment loss from road construction sites

Exposed soils associated with active construction sites provide opportunities for erosion and sediment transport during storm events, introducing risks associated with excess sediment to downstream infrastructure and aquatic biota. A better understanding of the drivers of sediment transport in construction site runoff is needed to improve the design and performance of erosion and sediment control measures (ESCMs). Eleven monitoring locations on 3 active road construction sites in central Ohio were established to characterize runoff quality from points of concentrated flow during storm events. Grab samples were analyzed for total suspended solids (TSS), turbidity, and particle size distribution (PSD). Median TSS concentrations and turbidity levels across all samples were 626 mg/L (range 25–28,600 mg/L) and 759 NTU (range 22–33,000 NTU), respectively. The median PSD corresponded to a silty clay loam, mirroring the soil texture of much of Ohio’s subsoils. TSS concentrations and turbidity were significantly positively correlated with the rainfall intensity 10 min prior to sample collection, suggesting that higher flow rates created greater shear stress on bare soil which resulted in more erosion. Conversely, rainfall duration was negatively correlated with particle size, indicating that prolonged moisture from rainfall promoted the dispersion of soil aggregates which mobilized smaller particles. Multivariable linear regression models revealed that higher rainfall intensities corresponded to higher turbidity values, while higher TSS concentrations were associated with higher rainfall intensities, depths, and durations. Results from this study highlight the importance of reducing raindrop impact and subsequent shear stress applied by concentrated flows through the use of ESCMs to limit sediment export from construction sites.

Numerical simulation of shelter effect assessment for single-row windbreaks on the periphery of oasis farmland

Dust storms, resulting from aeolian erosion, pose significant environmental hazards, while farmland is one of the main sources of dust storm release. An effective strategy to mitigate surface wind speed and curb dust emissions involves the establishment of windbreaks on the periphery of oasis farmland. This study conducts a series of numerical simulations using computational fluid dynamics (CFD) to explore the airflow fields around windbreaks with diverse systematic structural parameters, encompassing porosity, planting spacing, and fence effects. The main findings are as follows: (1) When the vegetation porosity is consistent (e.g., porosity α = 0.7, 0.8, and 0.9), exact geometry results can effectively reflect the distribution of wall shear stress, while the porous medium model overlooks these details. (2) The “Venturi effect” contributes to the acceleration of surface erosion and improper planting spacing results in an elevation of near-surface velocity. Planting spacing of 0.5 m demonstrates superior wind speed reduction performance, mitigating aeolian erosion and accumulation. (3) When the fence is positioned at l = 5h (h represents the height of the windbreaks), the flow field around the windbreaks is minimally influenced. The optimal placement distance for fences should be close to the windbreaks, featuring minimal porosity (l = 0 h, α = 0.1), extending the shelter distance from 3 to 4 h to 5–6 h. The research results can provide a theoretical basis for optimizing the plant configuration of biological desertification control and soil erosion control measures.