Search

Soil erosion is a hazard in every part of the world. The small-scale farmers often grapple with low agricultural production and food insecurity. This study was conducted to estimate soil loss in response to land use/cover change in 1990, 2000, 2010, and 2020 around Ghibe hydroelectric III dam in Southern Ethiopia. The Revised Universal Soil Loss Equation (RUSLE) model was applied using a geographic information system (GIS). Digital elevation model with 30 m to determine topographic factor and supportive practice (P) factor, rainfall from the National Meteorological Institute to calculate the erosivity (R) factor, a digital soil map of the world for erodibility (K) factor, and Landsat 5TM images of 1990, 2000, 2010, and the Landsat 8 OLI of 2020 to determine trends of land use/cover change and the cover management (C) factor were employed. The raster layers of topography, cover management, rainfall erosivity, soil erodibility, and conservation techniques were processed and multiplied using the GIS platform. The overall accuracy of supervised classification was 89.89. The results showed that the percentage of cropland and built-up areas increased by 11.93 and 32.44%, respectively throughout the three study periods. Conversely, the proportion of forest land, grassland, bare land, and bushland declined by 8.2, 9.3, 10.13, 8.6%, respectively. The average annual soil loss rates increased from 30.95 t ha−1 yr−1 in 1990 to 43.85 t ha−1 yr−1in 2020. This is significantly higher than the maximum threshold rate of erosion for Ethiopian highlands (11 t ha−1 yr−1). The local government officers, non-governmental organizations, and farmers who are trained should strengthen watershed management techniques. [ABSTRACT FROM AUTHOR]

The Zagora province in southern Morocco, characterized by its fragile Oasis-mountain-desert ecosystem, faces increasing threats from climate change. While the impacts of climate change on arid regions are widely acknowledged, location-specific studies analyzing future projections remain scarce, hindering the development of effective adaptation strategies. This study addresses this gap by examining historical temperature and precipitation trends in Zagora province from 1981 to 2021 and projecting their evolution to 2050 using time series modeling. An exponential trend model, demonstrating a high goodness-of-fit (R2 = 0.825), was identified as most effective for temperature forecasting, projecting a significant increase in mean annual temperature of + 1.1 °C (with a 95% confidence interval ranging from − 0.16 °C to + 2.45 °C) and in maximum temperature of + 1.65 °C (95% CI: +0.49 °C to + 2.82 °C) by 2050. An ARIMA (0,1,1) model with a constant best captured the historical precipitation patterns, revealing a projected increase in annual rainfall of 51.24 mm (95% CI: -25.59 mm to + 163.93 mm), potentially intensifying the risk of floods and soil erosion. These findings underscore a significant warming trend and a shift towards a more variable precipitation regime in the region. These projected changes, combined with a potential increase in rainfall intensity, threaten the sustainability of water resources, soil stability, and agricultural productivity in this already vulnerable region. This study provides essential quantitative data for informing adaptation decisions, guiding the implementation of effective strategies to preserve the Zagora Oasis ecosystem and the vital services it provides. [ABSTRACT FROM AUTHOR]

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 12.5 m 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−1 MJ−1 mm−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. [ABSTRACT FROM AUTHOR]

Tetracycline (TC), a widely used antibiotic, can easily enter aquatic ecosystems through soil erosion, livestock manures, and wastewater discharge, causes environmental and ecological health effects. AgCuFe2O4@Methylcellulose (MC)/Activated Carbon (AC) magnetic nanocomposite was synthesized accompanied by microwave-assisted co-precipitation procedure under green circumstances with high efficiency and subsequently utilized as a new heterogeneous magnetic nano-photocatalyst in the TC photodegradation from aqueous solutions. The structural characterization of AgCuFe2O4@MC/AC was performed by various analytical techniques. Afterwards, the key parameters of the photocatalytic TC degradation process, such as catalyst dose, TC concentration, pH, and process time, were investigated and optimized the results showed that the catalyst was synthesized on a nanometer scale (25 nm) with a quasi-spherical structure, with a high specific surface area, high magnetic strength (Ms = 19.27 emu g−1), and the preservation of the crystal structure. The removal efficiency of TC under optimal conditions including pH 7, initial TC concentration of 5 mg L−1, nano-photocatalyst dose of 0.5 g L−1, 90 min of irradiation time was reported to be 90.91% for synthetic sample and 87.17% for real wastewater sample. The removal effectiveness of total organic carbon was 85.2% under optimal conditions. The photocatalytic degradation kinetics of TC followed pseudo-first-order and Langmuir–Hinshelwood kinetic models, with values of KL–H = 0.633 L mg−1 and Kc = 0.126 mg L−1 min−1. After four cycles of recovery and regeneration, the synthesized catalyst demonstrated high chemical stability and was able to remove 62% of the pollutant. Finally, this study provides a viable approach for removing antibiotics using an AgCuFe2O4@MC/AC-based heterogeneous nanostructured photocatalyst. [ABSTRACT FROM AUTHOR]

The presence of livestock in riparian areas raises several questions about the conservation and sustainable use of water resources and biodiversity in Brazil. Although the Native Vegetation Protection Law (No. 12,651) focuses on riparian vegetation, protected as Permanent Preservation Areas (APPs), it does not exclude the presence of livestock in these fragile areas. Here, we provide an overview of APPs in Brazil and analyze the legal instruments that enable livestock in these areas, gathering the scientific evidence on associated environmental impacts. Currently, cattle in riparian areas represent a direct threat to biodiversity and ecosystem functioning and services, especially because these animals promote trampling, loss of vegetation, soil erosion, siltation, and pollution through urine and feces. To avoid cattle in APPs, legislation should be revised to implement more stringent restrictions; in parallel, alternatives for watering the animals must be sought, such as, for example, the installation of artificial ponds and drinking fountains. It would be appropriate to propose legislation or create incentives to fence livestock in pasture areas to preventing it from accessing APPs. Increasing cattle confinement is an alternative measure to traditional ranching in open pasture. Riparian zones represent a critical environment for biodiversity and society, so the presence of cattle and its associated negative impacts should be seriously considered by authorities. [ABSTRACT FROM AUTHOR]

With the advancement of urbanization, there has been a significant reduction in cultivated land, accompanied by soil erosion. Concurrently, the regularity of rainfall in recent years has been erratic, adversely impacting the grain economy and agricultural development in certain regions. Henan Province, spanning the basins of the Yangtze River, the Yellow River, the Huaihe River, and the Haihe River, possesses complex hydrological conditions and serves as a pivotal agricultural zone in China. Therefore, this paper utilizes daily rainfall data collected over 54 years (1969–2022) from 112 rain measuring stations in Henan Province to calculate the rainfall erosivity using the Zhang model and the erosivity model from the first national water survey. Meanwhile, spatial analysis was performed using the Kriging interpolation method in the ArcGIS Geostatistical Wizard, resulting in detailed spatial distribution maps of rainfall and rainfall erosivity. The study also employed Wavelet and Mann–Kendall tests to analyze the abrupt changes, trends and periodicity of rainfall and rainfall erosivity within the target region. The findings indicate that the average rainfall (1969–2022) in Henan province was 718.26 mm, while the average rainfall erosivity (R) was 3213.46 MJ mm/(hm2 h). R values are positively correlated with rainfall intensity and volume, displaying an annual upward trend. Spatially, R values increase gradually from northwest to southeast, closely aligning with topographical variations. Additionally, the analysis revealed a predominant periodic cycle of 54 years in the precipitation patterns. These results offer valuable insights for environmental and agricultural management in other regions of central China. [ABSTRACT FROM AUTHOR]

Urban rivers worldwide have been increasingly threatened by nitrate (NO3−) pollution. The Xianyang-Xi'an segment of the Weihe River, located in the loess plateau with serious soil erosion, has been highly urbanized and with intensive agricultural activities. Tracing the sources and transformations of NO3− is particularly challenging for this watershed which has multiple N sources and variable environmental factors. In this study, integrating antecedent studies with multiple stable isotopes and MixSIAR models, these river basins can be categorized into three classes: (1) urban areas, sewage, and manure were the predominant sources of NO3− in the Weihe River's mainstream, accounting for 73.4 ± 12.8%; (2) suburban areas, sewage and manure (Fenghe River, 58.0 ± 14.0%; Bahe River, 53.9 ± 15.0%) were recognized as the main sources of NO3−; (3) and the rural areas, ammonium nitrogen fertilizers were identified as the primary source of NO3− in the Heihe and Laohe Rivers. In addition, nitrification dominated the mainstream of the Weihe, Fenghe, and Bahe Rivers, while neither denitrification nor nitrification was evident in the Heihe and Laohe Rivers. In conclusion, this study is important for the improvement of surface water quality of rivers with different land use types and the development of targeted water environment management. [ABSTRACT FROM AUTHOR]

For maximization of soil and water quality benefits, the right agricultural conservation practices (CPs) should be practiced for the right place. The Agricultural Conservation Planning Framework (ACPF) is a tool that helps decision makers achieve precise conservation within a target watershed using rapid, low-cost Geographic Information System-based tools. ACPF takes the information on landscape characteristics and combines it with user input to identify locations susceptible to soil loss and water run-off and suggest potential CP locations. Suggested CPs may further be analyzed for urgency, installation cost, and effectiveness. In this study, ACPF was applied to analyze soil and water vulnerability within a small unglaciated sub-watershed in southwest Wisconsin and identify potential CP practices and recommended placement sites. To promote environmental sustainability in the agriculture sector, land managers are tasked with implementing CPs, but often lack adequate information on the most effective practice and placement strategy. Field-scale siting of CPs was achieved using high-resolution terrain derivatives and accurate simulation of the stream network. Slope disaggregation among soil loss vulnerability categories was also conducted. Greatest sources of vulnerability were associated with slope and erodibility factors, with average slope within cropped fields being 6% and erodibility being as high as 43%. Fields classified as critical for conservation had a mean slope of 7.4%. Suggested contour buffer strip (CBS) placement per field varied with slope, with steeper fields having denser placement. The results suggested that 3% of cropland could be removed from production if the recommended placement of CBS was implemented. A further 0.2% of the sub-watershed area would go to grassed waterways. The results support implementation of effective CPs based on local conditions and act as a tool to help reveal if existing practices in the sub-watershed are of a size and extent comparable to the predicted potential. [ABSTRACT FROM AUTHOR]

Global warming poses an unprecedented threat to agroecosystems. Although temperature increases are more pronounced during winter than in other seasons, the impact of winter warming on crop biomass carbon has not been elucidated. Here we integrate global observational data with a decade-long field experiment to uncover a significant negative correlation between winter soil temperature and crop biomass carbon. For every degree Celsius increase in winter soil temperature, straw and grain biomass carbon decreased by 6.6 (± 1.7) g kg-1 and 10.2 (± 2.3) g kg-1, respectively. This decline is primarily attributed to the loss of soil organic matter and micronutrients induced by warming. Ignoring the adverse effects of winter warming on crop biomass carbon could result in an overestimation of total food production by 4% to 19% under future warming scenarios. Our research highlights the critical need to incorporate winter warming into agricultural productivity models for more effective climate adaptation strategies. This study reveals that winter soil warming causes significant crop biomass carbon loss due to soil organic matter degradation. Ignoring this effect could lead to a 4-19% overestimation of future food production. [ABSTRACT FROM AUTHOR]

Soil erosion poses significant ecological and socioeconomic challenges, driven by factors such as inappropriate land use, extreme rainfall events, deforestation, farming methods, and climate change. This study focuses on the Kozhikode district in Kerala, South India, which has seen increased vulnerability to soil erosion due to its unique geographical characteristics, increase in extreme events, and recent land use trends. The research employs RUSLE (Revised Universal Soil Loss Equation), considering multiple contributing factors such as rainfall erosivity (R), slope length and steepness (LS), cover management (C), conservation practices (P), and soil erodibility (K). The study is unique and novel, since it integrates extensive field data collected from agricultural plots across Kozhikode with the RUSLE model predictions, providing a more accurate and context-specific understanding of soil erosion processes and also suggesting management strategies based on risk priority. The study found that Kozhikode experiences an average annual soil loss of 28.7 tons per hectare. A spatial analysis revealed varying erosion risk levels across the district. 52.0% of the area experiences very slight erosion, 10.31% has slight erosion, 6.18% undergoes moderate erosion, 3.88% is moderately severe, 7.34% is at severe erosion risk, 5.6% has very severe erosion, and 14.65% faces extremely severe erosion. Field data collected from agricultural plots across Kozhikode were compared with RUSLE-predicted values, revealing a low root mean square error, indicating a strong correlation between observed and simulated data. Based on these findings, the district was categorized into low, medium, and high-priority regions, with tailored recommendations proposed for each. Implementing these measures could mitigate erosion, preserve soil fertility, and support the long-term sustainability of natural and agricultural ecosystems in Kozhikode. Given the practical challenges in estimating RUSLE factors in Southern India, where data scarcity is a common issue, this preliminary study underscores the need for expanded, long-term field observations to enhance understanding of soil erosion processes at the watershed level. [ABSTRACT FROM AUTHOR]

Leakage at the bottom of an underground structure can compel ground water to form a converging flow, under which soil erosion may occur, thereby threatening the safety of the structure. Previous studies have shown that converging flow may induce backward erosion, and unravelling the mechanism behind this type of erosion was pivotal to mitigating disasters in practical engineering. Existing studies on this topic have been limited to monolayer erodible medium, while the mechanism behind the backward erosion of a multilayer erodible medium under converging flow remains unclear. In this study, both experimental tests and numerical simulations based on the validated computational fluid dynamics and the discrete element coupling method (CFD–DEM) were conducted to investigate the backward erosion of a multilayer sample under converging flow. The results demonstrated that the multilayer sample was eroded layer-by-layer, whereby residual layers could be observed at the bottom of the sample. The eroded regions in different layers were similar in shape but smaller in size for lower layers. In addition, particle exchange occurred among different layers during the erosion process. In general, lower-layer particles could directly ascend to upper layers in the eroded regions, whereas upper-layer particles mainly settled on the periphery of the eroded regions. [ABSTRACT FROM AUTHOR]

Inoculation of cyanobacteria has been studied as a valuable approach to promote soil stabilization and fertilization and counteract the erosion of marginal soils. One of the results of the inoculation of cyanobacteria is the formation of biological soil crusts, or biocrusts, which are complex soil communities playing a pivotal role in providing essential ecosystem services in drylands. While numerous studies have addressed the effects of different biocrust attributes on ecosystem functions, few studies have focused on the distribution of biocrust successional stages in the soil and their link with soil fertility properties. In this work, we investigated how the distribution of biocrust types (cyano-crust; cyano/moss crust, and moss crust) is related to soil nutrient status. We evaluated phototrophic abundance, exopolysaccharide production, and nutrient content in distinct biocrust types in an experimental area in the Hopq Desert, China, where their occurrence had been induced by cyanobacteria inoculation. In addition, we investigated the correlation between these variables. Photosynthetic pigment content, total carbohydrates, exopolysaccharides, organic C, and total N increased during the biocrust maturation stages. We found significant correlations between the levels of organic C, total carbohydrates, and total N with the abundance of diazotrophic cyanobacteria. Organic N was greater in the cyano/moss crust, while available P accumulated mainly in the cyano-crust. The three biocrust types are essential to each other as each represents a stage in which distinct nutrients are stored. This study complements previous studies by offering a more comprehensive view of how phototrophic variability in the distribution of biocrusts dominated by cyanobacteria or by mosses is closely interconnected with nutrient content and biocrust development. [ABSTRACT FROM AUTHOR]

Controversial aspects of production vs. conservation were profusely discussed globally by considering climate change and its impact on ecosystem services provision. However, previous meticulous livestock planning and short to medium-term ecosystem services monitoring make it compatible. This work aims to evaluate the effects of livestock on the quality of riparian forests, soil, and water in Nothofagus silvopastoral systems. Three river basins under livestock rearing were evaluated with different historic and actual stocking rates. Along three years, the physical, chemical, and bacteriological properties of soil, water, and quality of the riparian forest were evaluated. The basin without the presence of livestock showed the best quality of water and riparian forest. While the greater livestock stocking rate in riparian zones caused a deterioration of forest, decreasing the canopy cover, due to browsing and trampling of forest regeneration. In addition, livestock contributes faeces and urine into streams, producing the entry of sediment, nitrogen, phosphorus, and bacteria that negatively affect the quality of the water. The decrease of water quality is particularly accentuated in hot and dry years. However, Andean Patagonian streams and rivers have the capacity for self-purification of water with distances greater than 1,000 m without the presence of livestock, in which Escherichia coli disappears. On the other hand, sites with a higher livestock stocking rate, bare soil, and a lower degree of allophanization presented a greater turbidity in the water. To contribute to the goal of making silvopastoral systems production and ecosystem services supply compatible, we recommend livestock exclusion from the riparian zone, and keeping resilient areas under grazing with controlled stocking rates. Additionally, a monitoring program is necessary to prevent ecosystems from misfunctioning. [ABSTRACT FROM AUTHOR]

Ecologically clean small watersheds are crucial for water and soil conservation in China and provide a basis for the comprehensive development and sustainable utilization of water resources. In this study, a model and evaluation system for ecologically clean small watersheds based on the AHP-fuzzy comprehensive evaluation method were proposed to evaluate the construction of such watersheds in the Yangtze river estuary area of China, using Changning district in Shanghai as a case study. The evaluation system includes four attribute layer indicators: water quality, soil and soil erosion, pollution, and water system, as well as 13 index layer indicators. The watersheds are evaluated as "excellent," "good," "medium," or "poor." The evaluation is carried out by assigning weights to the indicators, establishing the membership degree matrix, determining the fuzzy synthesis operator, and calculating the score of the comprehensive evaluation. The evaluation results were analyzed and discussed. The results show that the comprehensive evaluation score of ecologically clean small watershed construction in Changning district was found to be 83.28. Pollution control received an "excellent"-level score of 86.21, while water system management received a "poor"-level score of 57.49. Overall, the construction of ecologically clean small watersheds was evaluated as "good," although some aspects still need improvement. The results of this study provide a basis for evaluating the construction of ecologically clean small watersheds in the Yangtze river estuary area. [ABSTRACT FROM AUTHOR]

Natural hazards, such as flood, landslide, and erosion, are the reality of human life. spatial prediction of these hazards and their effectiveness factors are extremely important. The main goal of this study was to prepare multi-hazard probability mapping (flood, landslide, and gully erosion) of the Gorganrood Watershed. In addition, different machine learning models such as Random Forest (RF), Support Vector Machine (SVM), Boosted Regression Tree (BRT), and Multivariate Adaptive Regression Spilines (MARS) were applied. First, a flood, landslide, and gully erosion inventory map was produced using GPS in the field surveys and Google Earth. Factors affecting the hazards were identified, and GIS maps were prepared. The MARS model (AUC = 99.1%) provided the highest predictive performance for flood, landslide, and gully erosion hazards. However, for flood and landslide, the RF model exposed excellent and good performance, respectively. According to the variable importance analysis, drainage density (89.4%), digital elevation model (30.5%), and rainfall (41.7%) were consistently highly ranked variables for flood, landslide, and gully erosion, respectively. Multi-hazard maps can be a valuable tool for the conservation of natural resources and the environment, as well as for sustainable land use planning in multi-hazard-prone areas. [ABSTRACT FROM AUTHOR]

The purpose of this research was to model areas prone to erosion in the Gol-Mehran catchment in southern Iran. For this purpose, the soil erosion map was determined using membership functions and analytic hierarchy process (AHP) determined the soil erosion map. Additionally, using the self-organizing map (SOM) and principal component analysis (PCA) methods, the most crucial parameters affecting gully erosion were extracted. Finally, soil erosion was predicted using a multilayer perceptron (MLP) and radial basis function. The results of the fuzzy AHP method with all data and the selected data with SOM and PCA demonstrated that areas located in the center of the region were prone to gully erosion. The results of this research also demonstrated that urban lands have expanded significantly, while vegetation has decreased from 1990 to 2019, which has had a significant impact on soil erosion. The results also showed that the MLP model, with R2 = 0.97, could accurately predict soil erosion. [ABSTRACT FROM AUTHOR]

This study examines how acid rain affects the microstructure and mechanical properties of cement-amended loess, crucial for ensuring the safety of engineering projects. We aimed to investigate how acid rain influences the micro-mechanical behavior of cement-amended loess and its damage characteristics under combined acid rain and loading conditions. Cement-amended loess samples were exposed to artificial acid rain with varying pH levels, and changes in their strength and microstructure were analyzed using unconfined compression tests, SEM, NMR, and XRD techniques. Our findings reveal that acid rain erosion of cement-amended loess triggers hydration and erosion reactions. As acid rain concentration increases, the unconfined compressive strength of the amended soil gradually decreases, accompanied by an expansion of pore spaces from small to large-medium pores. Additionally, particle contacts shift from face-to-face and side-to-side to point-to-point and side-to-side configurations. Furthermore, prolonged erosion time exacerbates pore space expansion, indicating a time-dependent effect on soil integrity. To characterize these effects, we developed a constitutive equation within the framework of damage mechanics that incorporates both erosion and loading. This equation successfully aligns with experimental data, providing a comprehensive understanding of the coupled effects of acid rain erosion and mechanical loading on cement-amended loess. These insights are pivotal for designing resilient engineering solutions in environments prone to acid rain erosion. [ABSTRACT FROM AUTHOR]

India, a subtropical country, also has relatively more environmental problems because of intense rainfall that occurs quickly, as well as other natural and man-made causes of soil degradation. The use of predictive models in GIS is observed beneficial for computing the virgin net soil erosion as well as deposition. Thus, the study aims to evaluate the spatial long-term average annual soil erosion (gross soil erosion rate), net soil erosion as well as a deposition for the east-flowing Cauvery River Basin (CRB) using RUSLE integrated with the TLA-SDR model in Geographic Information System (GIS) at recent (2020 to 2022) periods. The estimation of gross soil erosion rates (A) ranges between 0 and 94,194.4 t h−1 year−1, mean of ~ 223 t h−1 year−1. The sediment yield (SY) of CRB varies from 0 to 10,895.4 t h−1 year−1 with a mean of 26 t h−1 year−1. Moreover, the transport capacity (TC) of CRB varies between 0 and 5,339,136 t h−1 year−1, with a mean of 16 t h−1 year−1. Further, net erosion is estimated with TC and deposition which has an average value of ~ 4.5 t ha−1 year−1 (i.e., ~ 2% of the gross erosion), of which 1.15% of CRB shows very severe erosion while 56.68% shows high deposition. The study also addresses the effect of various LULC types on soil loss and reveals that barren rocks have the highest soil loss, followed by forest, build-up, barren land, agricultural land, and plantation. Likewise, the study assesses whether rapid climate change may exacerbate erosion rates and concludes that greater erosion rates are recorded with rising rainfall. Additionally, when comparing the total erosion to total sediment yield rate of CRB with major basins like Ganga (GBA) and Kosi (KB), signifying the topographical, climatic as well as tectonic setup of the region. The study's findings will be an important tool for decision-makers as they execute management plans over the CRB, and this technique will used broadly to identify management methods in river catchments worldwide. [ABSTRACT FROM AUTHOR]

A study was conducted on the soil erosion process in the Baitarani River Basin in peninsular India, using two distinct methodologies based on drainage basin morphometry. The study covered 16 sub-basins, and evaluated the soil erosion dynamics using sixteen linear, areal, shape, and relief features. Weighted sum analysis (WSA) and a hybrid model named principal component based weighted sum analysis (PCWSA) were used to analyse the morphometry data and establish the likelihood of soil erosion occurrence. The results showed that based on the WSA approach six, four and six sub-basins had low, moderate and high flood priorities respectively, while based on the PCWSA technique five, six and five sub-basins had low, moderate and high flood priorities respectively. For quantitative validation MLR models were obtained using these two approaches based on USLE model based annual average soil erosion magnitude, and the derived values exhibit acceptable accuracy (48.2% and 55.2% respectively) in modelling soil erosion. The results showed that the PCWSA approach could produce better accuracy with only six principal components, compared to the WSA method with six uncorrelated factors. For qualitative validation, satellite data based Modified soil-adjusted vegetation index (MSAVI) map was applied which confirmed satisfactory agreement with the proposed approach. [ABSTRACT FROM AUTHOR]

Identifying soil erosion-prone zones in an ungauged river basin is crucial for devising and implementing timely soil protection measures to mitigate soil degradation and protect soil quality. Soil erosion damages the fragile ecosystem, decreases soil fertility, and reduces reservoir water storage, thereby impacting food production. The prime motive of the current research work is to assess and categorize on the basis of priority the sub-watersheds (SWs) susceptible to substantial soil erosion in the Ponnaniyar River basin (an ungauged river basin) based on the morphometric parameters that impact soil erosion. To achieve this research objective, four multi-criteria decision-making (MCDM) approaches based on the outranking approach and synthesis method are adopted to facilitate the decision-making process by considering an integrated and balanced assessment of multiple complex parameters for devising effective soil conservation measures to minimize soil erosion. Cartosat-1 digital elevation model (DEM) is employed to extract eighteen morphometric parameters under linear, shape, areal, relief and hypsometric aspects. The priority of SWs obtained by different MCDM techniques is evaluated using percentage of variation and intensity of variation. The outcomes show that the MABAC method is effective in prioritizing SWs with the least percentage of variation (59.61%) and intensity of variation (4.397). It is also found to be the best method for integration with the RSS method for determining SW priority with a root sum of squares value of 43. SW1 is identified to be highly vulnerable to soil erosion with a grade average value of 1.00 followed by SW2 (3.00), SW3 (3.25) and SW13 (5.00), requiring immediate implementation of watershed planning and management measures to control the extent of soil erosion and safeguard soil resources. [ABSTRACT FROM AUTHOR]

Purpose: The relations between rill morphology indicators and particle size selectivity by rainfall events were investigated, providing a new perspective on the mechanism of rill morphology indicators impacting on rill erosion processes. Materials and methods: Indoor rainfall experiments were carried out with three-dimensional (3D) laser scanning technique for better monitoring the rill morphological indicators, using two types of soil collected from the north part and the south part of the Loess Plateau, respectively. Results and discussions: The higher degree of headward erosion is occurred on loamy clay (LC) soil from the south part of the Loess Plateau with the higher total length (6.65 m) due to the higher clay content. Higher degree of side erosion is demonstrated on sandy loam (SL) soil from the north part of the Loess Plateau with the higher mean rill width (0.09 ± 0.00 m) due to the higher sand content. The ratios of rill width to depth do not show significant differences on two types of soil with the average value greater than 1, indicating the relatively higher degree of side erosion than downward erosion on both soils. Silt fraction is selected with much higher efficiency than other fractions in two types of soil due to the dominant silt fractions in the primary soil. Rill width (W) is the most sensitive indicator to the particle size selectivity, as both the contents of clay, silt and fine particles and the enrichment ratio of silt show significantly (P < 0.05) positive correlations with W. While, the enrichment ratio of sand fraction shows significantly (P < 0.05) negative correlations with rill maximum depth and degree of contour line departure. Conclusions: The differences of rill morphology indicators on two types of soil slope mainly depend on soil texture and the development processes of rills. [ABSTRACT FROM AUTHOR]

Sediment loss and export pose significant global environmental issues, profoundly affecting water quality, soil fertility, and ecosystem stability, particularly in vulnerable mountain ecosystems like the Indian Himalayas. The present study used remote sensing data and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) sediment delivery ratio (SDR) model to analyze spatial–temporal variations in soil loss (SL), sediment export (SE), and sediment retention (SR) capabilities in the South Shimla watershed, Himachal Pradesh, India, from 1993 to 2023. The findings showed significant changes in land use and land cover (LULC): evergreen forest and scrub land decreased sharply by 11.53% and 36.43%, respectively, while agricultural areas and built-up areas increased notably by 71.16% and 215.76%, respectively. Despite a decline of 19.18% in SL and 24.43% in SE, sediment loss and export varied across the study area, highlighting the heterogeneous nature of sediment dynamics. The overall retention capacity increased by 2.59%, with scrub forests playing a critical role in SR, while built-up areas showed the lowest retention. Northern and central sub-watersheds (SWs) experienced a significant decrease in retention capacity (from − 1.92 to − 11.6%), whereas those in the southern and eastern regions saw an increase in SR (from 3.69 to 28.24%). These results underscore the complex interactions between LULC changes, sediment dynamics, and retention services, highlighting the importance of preserving natural ecosystems and informing policy for landscape-based conservation and development planning in the vulnerable Himalayan region. [ABSTRACT FROM AUTHOR]

A study was conducted at Punjab Agricultural University, Ludhiana, Punjab, with the aim of monitoring soil loss and infiltration rate in loamy sand soil. The study focused on the effects of applying polyvinyl alcohol (PVA) and mulch under simulated rainfall conditions. The experimental setup involved testing three levels of PVA (0.5%, 0.75%, and 1.0%), one level of wheat-straw mulch (600 g/m2), and a Control treatment (untreated soil). Each of these treatments was replicated four times. The lowest soil loss (20.9 g/m2) was recorded under the 1.0% PVA treatment, while the highest (120.1 g/m2) was seen under the 0.5% PVA treatment. The 1.0% PVA treatment showed a significant reduction in soil loss compared to the 0.5% PVA, 0.75% PVA, mulch, and Control treatments, with reductions of approximately 82.6%, 45.1%, 81.2%, and 89.6%, respectively. Regarding infiltration rates, the Control treatment exhibited the lowest rate (2.4 cm/h), while the 1.0% PVA treatment displayed the highest rate (9.6 cm/h). Additionally, the use of mulch led to a 44.7% reduction in soil loss compared to the treatment without mulch, likely due to the mitigated impact of raindrops. The infiltration rate was significantly higher (4.8 cm/h) under the mulched treatment compared to the unmulched treatment (2.4 cm/h). Overall, the application of PVA and mulch resulted in a drastic reduction in soil loss, likely attributable to the enhanced stability of soil aggregates, improved infiltration rate, and reduced runoff. [ABSTRACT FROM AUTHOR]

Soil erosion has been recognized as a critical environmental issue worldwide. While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective, there is a notable gap in understanding the intricate interplay between natural and socioeconomic factors, especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions. To address this, our study evaluates the soil erosion vulnerability at a provincial scale, taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors. We developed an evaluation index system based on 15 indicators of soil erosion vulnerability: exposure, sensitivity, and adaptability. In addition, the combination weighting method was applied to determine index weights, and the spatial interaction was analyzed using spatial autocorrelation, geographical temporally weighted regression and geographical detector. The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020. The soil erosion vulnerability increased before 2000 and then. The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province (Xiantao, Tianmen, Qianjiang and Ezhou) with obvious spatial aggregation that intensified over time. Natural factors (habitat quality index) had negative impacts on soil erosion vulnerability, whereas socioeconomic factors (population density) showed substantial spatial variability in their influences. There was a positive correlation between soil erosion vulnerability and erosion intensity, with the correlation coefficients ranging from -0.41 and 0.93. The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity. [ABSTRACT FROM AUTHOR]

Lishu County, which is located in the black soil region of Northeast China, represents a key site for the analysis of soil erosion intensity. This study offers a scientific foundation for the development of targeted soil and water conservation strategies within the region. The Revised Universal Soil Loss Equation (RUSLE) was employed to compute the soil erosion modulus in Lishu County, with the objective of conducting a quantitative analysis of the temporal and spatial distribution patterns of soil erosion. Additionally, the changing characteristics of soil erosion were examined from the perspectives of land use types and slope variations. The Generalized Connectivity Causality Model (GCCM) was utilized to identify the causal relationship between soil erosion and land use types through the reconstruction of state space and cross-mapping predictions. (1) Soil erosion in Lishu County between 2000 and 2020 predominantly exhibited mild to moderate levels, characterized by patchy and sporadic erosion, with relatively severe occurrences in the northern and central regions. (2) Soil erosion was correlated with land use and slope variations, with more than 90% of erosion incidents transpiring in cultivated land areas. The 3°-5° slope range in Lishu County emerged as a focal point for erosion, necessitating targeted prevention and control measures. (3) The GCCM model illustrated a discernible causal relationship between soil erosion and land use, revealing mutual influences between the two factors. Between 2000 and 2020, both the area and intensity of soil erosion in Lishu County exhibited an initial increase, followed by a subsequent decrease. This suggests an overall trend of amelioration in soil erosion conditions. However, notable spatial disparities persist in the erosion distribution across the region. [ABSTRACT FROM AUTHOR]

Groundwater pollution from subsurface leaching of eroded soil, pesticides and fertilizers under agricultural fields are deteriorating the quality of groundwater. In this connection, this study aimed to prepare a groundwater vulnerability map using the DRASTIC (Depth to water table, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone media and hydraulic Conductivity) model to evaluate the soil erosion and groundwater quality relationship under soil erosion prone areas of the Panjkora river basin in the northern Pakistan. In this model, relative weights between 1 and 5 are assigned (5 being the most important) to D-R-A-S-T-I-C variables that may affect groundwater quality. According to the results, 72161.64 Hectares (ha) of the study area is low vulnerable to contamination, 144828.70 ha area is slightly moderate vulnerable, 239582.22 ha area is moderate vulnerable, 121769.37 ha area is high vulnerable, and 944.61 ha area is very high vulnerable to groundwater contamination. Groundwater samples from soil erosion hotspots were examined to establish a correlation between soil erosion and groundwater contamination. Total dissolved solids (TDS) and NO2 concentration in some areas were found to be higher than the World Health Organization (WHO) permissible limits. Soil erosion exhibited a positive correlation with groundwater contamination with correlation coefficient (r) of 0.89, root mean square difference (RMSD) of 2.24 and bias of 0.094. The DRASTIC model was validated through ROC AUC curve (score = 0.62). This study is a first attempt to evaluate the inherent groundwater vulnerability and sensitivity to pollution in this region with severely declining groundwater quality due to several unexplored reasons. [ABSTRACT FROM AUTHOR]

A precise land suitability assessment plays a vital role in modern agriculture to sustain production against population explosions worldwide without affecting natural resources or environmental factors. Further, recent urbanization has led to a reduction in arable land and forced the conversion of non-arable land to arable land. Therefore, developing land suitability with its potential and limitations is essential through advanced techniques like multi-criteria Decision Analysis for the particular area. The current research aimed to assess the land suitability of the Manimutha Nadhi watershed, Tamil Nadu, India, using geographical information system (GIS) and Analytic Hierarchy Process (AHP) methods. This study area, Manimutha Nadhi, covers a total area of 263.89 km2. Using a random sampling technique, 57 soil samples were obtained. The parameters for the AHP study were soil pH, EC, Soil organic carbon (SOC), available NPK, soil texture, and soil erosion. The climatic parameters, Annaula average rainfall (AAR) and Annual average temperature (AAT) and topographic parameter slope of the study area are also used as the criteria for generating final agricultural land suitability. The final suitability map through GIS and AHP was created using weighted overlay analysis. The land suitability class on the basis of FAO classification is highly suitable (S1), moderately suitable (S2), marginally suitable (S3), currently not suitable (N1), and permanently not suitable (N2) for agriculture. The results of the final land suitability map by AHP and GIS revealed that 150.58 km2 (57.09%) of the research region is highly suitable for agriculture (S1). The 29.60 km2 (10.08%) area was moderately suitable (S2) for irrigated agriculture. The 53.37 km2 (20.20%) area was marginally suitable (S3) for irrigated agriculture. The 10.56 km2 (7.53%) area was currently unsuitable (N1) for agricultural uses. The area of about 13.45 km2 (5.10%) was permanently unsuitable (N2) for agriculture. The outcomes can be used as baseline information on the land that could strengthen agriculture production in the Manimutha Nadhi watershed. [ABSTRACT FROM AUTHOR]

Hilly and mountainous regions are significantly impacted by soil erosion, primarily due to rainfall-runoff processes occurring on the hillslope scale. Assessing soil erosion is crucial for quantifying the loss of soil carbon and nutrients, which diminishes the potential of soil ecosystem services and is critical for mitigating the impacts of climate change on food security. However, the Himalayan landscape poses serious challenges for assessing soil erosion due to its steep and rugged terrain, which hinders the use of conventional and modelling methods. The fallout radionuclide—137Cs has been extensively utilized as an environmental marker for investigating soil redistribution processes. Despite its potential, there is a notable lack of 137Cs-based soil erosion studies in the Himalayan region. In this context, we assessed the applicability of the fallout radionuclide—137Cs method in quantifying soil erosion rates and identifying erosion hotspots on two hillslopes of the Higher Himalayas. On the hillslope scale, we observed that soil erosion rates vary based on slope gradient and land use/land cover. Forested areas exhibited the lowest soil erosion rates compared to cultivated areas, while flat hillslope positions experienced lower erosion rates than steeper positions. The average net erosion rate for the Harsil hillslope varied among different hillslope positions, ranging from – 2.9 to – 15.6 t ha−1 yr−1. Similarly, in the Gangnani hillslope, the net erosion rates varied across different positions, ranging from – 5.6 to – 39 t ha−1 yr−1. Our findings confirm that the middle and lower hillslope positions are the most critical source areas with higher soil erosion rates, while hillslope positions with forest cover demonstrate the lowest erosion rates, identified as helpful in controlling soil erosion. The study has demonstrated the applicability of FRN as a soil erosion measurement method in the complex, rugged, and steep terrain of the Himalayas, highlighting the need for targeted conservation efforts to mitigate soil erosion and preserve ecosystem integrity. [ABSTRACT FROM AUTHOR]

The transformation of radioactive contamination of agricultural lands with 137Cs isotope is one of the evidences of soil erosion. Changes in the radionuclide content and the corresponding rates of soil loss can be assessed quantitatively by repeated soil sampling at key sites over long time intervals. Being highly labor-consuming, such studies are few in number; they have not been conducted previously in the zone of intense Chernobyl contamination in the Central Russia. The method of repeated sampling (resampling) was used in 2023 within the plowed slopes of a small catchment in the southern part of Tula region, 26 years after the first sampling in 1997. The changes in 137Cs deposits (kBq/m2) that occurred during this period turned out to be statistically significant, with an average reduction of more than 10%. According to a proportional erosion conversion model based on relative changes in 137Cs deposits, the average annual rate of washing off was estimated at 11.7 t /ha. Such values of soil loss are comparable in general with the previously published results of independent mathematical modeling for this area. Thus, the use of resampling method, including that at new sites, appears to be promising for assessing the rate of soil loss. In addition, it permits us to verify the existing erosion models and to trace long-term trends in the spatial transformation of radioactive contamination. [ABSTRACT FROM AUTHOR]

One of the important areas of soil erosion science is the development of soil conservation measures. The analysis of published works shows that in Russia most of the techniques and methods to control soil erosion were developed in the 1960s–1980s. In recent decades, interest in scientific and practical developments in this area has been declining. Published data on erosion control measures are poorly systematized, and their generally accepted classification is absent. The typification of erosion-control measures proposed by the authors made it possible to systematize all these measures found in the works and to create their register in the form of a table. Information about the efficiency of erosion control measures is scarce and contradictory. The results of agrotechnical measures are best studied. Non-inversive tillage is the most efficient among agrotechnical measures, it helps to reduce soil erosion by 70–90% according to published data; other agrotechnical measures, on average, reduce the rate of soil erosion by half. Climate change and socioeconomic transformation in the agricultural and industrial complex of Russia in recent decades have led to significant changes in the rate and volume of soil erosion. However, the analysis of literature indicates a shortage of works aimed at adapting existing erosion control measures, or developing new measures with due account for global and regional changes in erosion/deposition processes. [ABSTRACT FROM AUTHOR]

The impact of land use and erosion-deposition processes on some physical, chemical, and biological soil properties in a small agricultural catchment in Kursk oblast is analyzed. Plowed Haplic Chernozems and stratozems (Fluvic Chernic Phaeozems (Loamic, Pachic)), as well as unplowed stratozems of a dry valley bottom have been studied. The proportion of large soil aggregates (clods) >10 mm in soils is high on plowed land and low in the dry valley bottom. Differences in the carbon and nitrogen content and in the C/N ratio have not been detected. The analytical pyrolysis has revealed 26 pyrolysates in the composition of soil organic matter (SOM). The relative abundances of pyrrole, pyridine, toluene, and indan among SOM pyrolysates are higher in plowed soils as compared to the soils at the dry valley bottom. Proportions of furfural and methyl furfural among SOM pyrolysates are higher in soils of the dry valley bottom than in plowed soils. Differences in the content of alkanes and phenol are absent. The biomass of microorganisms is mainly formed by fungi (97–99%), and their abundance is greater in soils of the dry valley bottom than in soils of the plowland. Differences in the respiratory activity of the studied soils have not been revealed. The significant influence of erosion-deposition processes and soil cultivation on the spatial heterogeneity of the SOM composition and microbiological parameters is shown. Plowed soils are characterized by the high relative abundance of nitrogen-containing SOM components, while soils at the dry valley bottom have a relatively high abundance of carbohydrate components of mature SOM. The accumulation of fungal biomass and an increase in the structure coefficient in soils of the dry valley bottom indicate the participation of material redeposited from slopes in soil aggregation. [ABSTRACT FROM AUTHOR]

In an area like India, where a large number of people are dependent upon agriculture, soil erosion assumes the role of a silent killer. A comprehensive soil management plan requires systematic development and planning at the scale of the natural boundaries, i.e., the watersheds. These watersheds are now actively encouraged to become the planning unit for a wide range of natural resource management. Sub-basin prioritisation with respect to erosion susceptibility, therefore, has become increasingly popular in the last few decades as this helps in optimal distribution, especially in a country like India, where the availability of resources is scarce. Erosion is a complex problem wherein a large number of factors play an important role in influencing this process. Therefore, multi-criteria decision-making (MCDM) techniques are becoming more popular in this domain. However, there are a myriad of MCDM models in literature, and a proper and systematic comparison between such MCDM models may help in deciding on the best possible model in the given categories. This paper has tried to make such a comparison for morphometry-based sub-basin prioritisation in the rocky terrain of the Chaka River Basin, Eastern India. The MCDM models that have been investigated include technique for order of preference by similarity to ideal solution (TOPSIS), VlseKriterijumsk Optimizacija Kompromismo Resenje (VIKOR), multi-objective optimisation on the basis of ratio analysis (MOORA), compound factor (CF), weighted sum model (WSM), weighted product model (WPM) and weighted aggregated sum product assessment (WASPAS). These results were compared with respect to the RUSLE-based annual soil loss of the Chaka Basin with the help of the ROC curve. Results reveal that the MOORA MCDM method is the most reliable (AUC = 0.711), whereas the TOPSIS is the least authentic (AUC = 0.378). The middle domain of the Chaka Basin appears to be highly prioritised as compared to the lower domain. [ABSTRACT FROM AUTHOR]

This study aimed at investigating the harm from ecosystem services (ESs) according to agricultural land conversion (ALC) by using meta-analysis. The results of meta-regression showed that spatiotemporal effects had significant influences on some ES losses, and the maximum spatial impacts were relevant to Asia and Europe. Moreover, the results of ALC rate coefficients in meta-regression indicated that three large losses of ES were related to soil erosion (0.314), air pollution (0.202), and climate change (0.161). Therefore, the ALC should be done at a suitable conversion rate to reduce ES losses. Accordingly, administrators are suggested to consider careful research planning for the ALC in the process of economic development. Other strategies highlighted the importance of ALC–ES interactions for human well-being, such as measuring the pricing of goods and services based on land resources, continuously monitoring illegal ALC, and imposing taxes on unplanned ALC. [ABSTRACT FROM AUTHOR]

Tunnel excavation in short distance will change the physical equilibrium stress field of stratum and cause adverse effects on adjacent existing pile. In this paper, a simplified analytical solution is thus proposed to evaluate the existing pile behaviors due to adjacent tunnel excavation. First, tunneling-induced horizontal free field soil movement calculated by a modified Loganathan's formula during shield tunnel excavation is presented. Then, consider that the existing pile is a Euler–Bernoulli beam resting on the Pasternak foundation model. The differential equation of lateral displacement of existing pile is established by combining the coupling condition of soil-pile interaction. Finally, the analytical solution of lateral displacement of the existing pile caused by adjacent tunneling is obtained by finite difference method. The reliability of the analytical solution is validated by comparing with boundary element program, finite element simulation and field measurements. Parametric studies are also preformed to estimate the effects of various factors on an existing pile, including the clearance distance, tunnel depth, tunnel radius, pile diameter and tunneling-induced soil loss rate. A prediction formula for evaluating the maximum lateral displacement of a pile caused by adjacent tunneling was presented, which the deviation rate between predictions and the results of published case reports is less than 10%. [ABSTRACT FROM AUTHOR]

In Iran, particularly in the Zagros forests, natural land uses are increasingly being converted into agriculture, which can negatively influence soil hydrological processes. To study this, three replicate micro-plots were installed on similar slopes in the forest (FO), rangeland (RA), and vineyard ‒ under the canopy (VUC) and in the inter-row space (VIR) ‒ to measure soil loss and surface runoff. Top- and sub-soil samples were randomly taken in three replicates from three sites for each land use/cover (LUC). Standard laboratory methods were utilized to measure the designated soil properties. According to the results, soil organic matter (SOM), aggregation indices, residual (ϴr) and saturated water content (ϴs), water content at field capacity (ϴFC), and saturated hydraulic conductivity (Ks) showed a significant decreasing trend as follows: FO > RA > VUC > VIR, whereas EC, pH, CaCO3, bulk density, and K-factor significantly showed an increasing opposite trend. LUC did not affect permanent wilting point (ϴPWP), available water content (AWC), and α and n van Genuchten's parameters. It was also found that RA and FO exhibited a higher repellency index than VUC and VIR. The forest had the lowest soil loss and runoff due to its higher porosity, SOM, aggregate stability, infiltration rate, water storage capacity, and surface cover. The highest soil loss and runoff were observed in VIR because of the vineyard's management operations and the bareness of soil between the vine rows. Conservation measures, such as no-tillage, mulching, or cover crops in the inter-row spaces, are recommended to mitigate these negative effects. [ABSTRACT FROM AUTHOR]

Water erosion is one of the most extensive processes of soil and land degradation. This process significantly deteriorates the quality of ecosystem services provided. Studying the mechanism and consequences of this phenomenon will help develop strategies to mitigate its impact on the environment. One of the challenges in studying water erosion is the high cost of conducting field research over large areas. Another challenge is the limitation of existing models, which are often developed for specific regions. Our research aims to address these problems by adapting the widely used RUSLE2 model to local conditions. Beijing was chosen as the study area due to its rich information resources and extensive results from field measurements of soil water erosion. Calculations were performed using a raster data model, which included a slope angle model, slope length, soil erodibility, rainfall erosion potential factors from precipitation and snowmelt, land use types, and vegetation cover management factors. All data were taken from open sources. The average soil erosion in the studied area was 25 t · ha–1 per year. The discrepancy with other studies was less than 1%. The modified RUSLE2 model showed good results, correlating with other studies in this area. [ABSTRACT FROM AUTHOR]

Land degradation is a global problem of mankind, the greatest contribution to which belongs to aridity and soil erosion. The social consequences of land degradation are extremely important, but poorly conceptualized issues. This makes it difficult to create effective research programs to study them. The article provides an overview of the issues under consideration. An expert study was conducted to identify a problem field in the field of studying the social consequences of land degradation. By interviewing nine recognized scientific experts in the field of land degradation studies, the most reliable judgments were identified, which served as a basis for highlighting the main forms of manifestation of the social consequences of land degradation. Private research concepts were compiled, which consist in highlighting the position of each expert on the main consequences of land degradation. As a result, a generalized expert model of the problem field of the social consequences of land degradation was formed. According the model all experts note the interdisciplinary nature of the study of the issues under consideration, which are placed at the intersection of environmental, economic, and social problems. The overwhelming majority of experts noted the direct nature of the effect of land degradation on the formation of social consequences. Thanks to the integration of individual ideas, it was possible to identify characteristics for which there are discrepancies. This provides an opportunity for a broader study of the social consequences of land degradation. However, there is an expert opinion that the social consequences are rather indirect and are realized through resource problems. Some experts draw attention to the fact that there are the extreme forms of land degradation that significantly increases the manifestation of social consequences. According to experts, land degradation can lead to change in social status, a decrease in the recreational potential of land, hunger, a change in life expectancy and loss of jobs, increased stratification of society, changes in the cost of housing and a change in the type of land use, reduction in the use of land for agricultural needs, and changes in people's attitudes to more individualistic ones. It was also noted that the use of products from degraded lands could lead to an increase in cancer incidence in the region. Conceptualization and identification of these problems could help to focus efforts in the field of studying the social problems of land degradation. [ABSTRACT FROM AUTHOR]

Despite the large number of different antierosion practices used in the country, the dynamics of the areas of eroded lands remains multidirectional and unstable. The goal of the work was to propose a methodological approach for semantic modeling of sustainable land management with a focus on antierosion measures, the methods for such modeling and land management in the areas prone to soil erosion in order to maintain and restore degraded lands. A variety of erosion control techniques, methods, approaches, technologies and activities described in different sources, including databases on best practices, educational and scientific literature serves as objects of the study. The study was based on the integration of several working hypotheses and approaches proposed by the authors in earlier publications. The methodological basis of these approaches is the concept of land degradation neutrality (LDN) and the principles for assessing the "sustainability" of environmental management based on it. Using the example of several sites, methods for semantic modeling of the sustainability of antierosion land management are considered. These methods are based on assessing the achievement of LDN using so-called "good" practices. For the assessment, the following parameters of the model were applied: "natural potential" (reflecting resource potential, adaptive potential and the ability to self-recovery of land), "expanded potential" (reflecting human improvements in natural potential and the sufficiency of socioeconomic conditions); "actual adverse impacts," including natural processes and phenomena and those caused by human impact; and "potential adverse impacts," including natural and anthropogenic risks. Model parameters can be combined in the required combination and reflect different modeling tasks in order to determine the adequacy of erosion control practices, including general approaches and techniques for regional models, methods and technologies for subregional and local ones, and specific activities and measures for local models implemented for individual land plots and farms. The proposed method for visualizing models, based on the construction of radar diagrams, is a flexible solution that provides opportunity to consider the sufficiency of practices, combine them into groups, and also generalize sustainability parameters depending on the goals of modeling. [ABSTRACT FROM AUTHOR]

Soil erosion, as a type of land degradation, affects various human economic interests. It is shown that the most promising areas of erosion studies where economic methods can be applied are assessment of actual damage from soil erosion, determination of the amount of probable damage from erosion processes in soils, and economic analysis in the development of sustainable land use systems for areas with soils subject to erosion. The group of methods for determining economic damage, including those which take into account ecosystem services that soils "lose" as a result of erosion processes, is characterized by the greatest development. Methods for assessing the risk of soil erosion have a significant development potential, since an extensive database of predictive models and equations (USLE, RUSLE, RUSLE-2, WEPP, EUROSE, CREAMS, EPIC, VNIIZiZPE, etc.) has been created, which make it possible to assess indicators of soil erosion in the future. Sustainable land use systems are developed using the neoclassical capital theory, which requires that the fertility of soil and net social benefits from nonmarket goods and services from agricultural lands should be maintained over time. Thus, it is possible to create compensatory taxation mechanisms for areas with the manifestation of soil erosion processes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Climate change poses an immediate threat to tropical soils with changes in rainfall patterns resulting in accelerated land degradation processes. To ensure the future sustainability of arable land, it is essential to improve our understanding of the factors that influence soil erosion processes. This work aimed to evaluate patterns of soil erosion using the activity of plutonium isotopes (Pu) at sites with different land use and clearance scale in the Winam Gulf catchment of Lake Victoria in Kenya. Erosion rates were modelled at potential erosive sites using the MODERN model to understand small-scale erosion processes and the effect of different management practices. The lowest soil redistribution rates for arable land were 0.10 Mg ha−1 yr−1 showing overall deposition, resulting from community-led bottom-up mitigation practices. In contrast erosion rates of 8.93 Mg ha−1 yr−1 were found in areas where steep terraces have been formed. This demonstrates the significance of community-led participation in effectively managing land degradation processes. Another key factor identified in the acceleration of soil erosion rates was the clearance of land with an increased rate of erosion over three years reported (0.45 to 0.82 Mg ha−1 yr−1) underlining the importance vegetation cover plays in limiting soil erosion processes. This novel application of fallout plutonium as a tracer, highlights its potential to inform the understanding of how soil erosion processes respond to land management, which will better support implementation of effective mitigation strategies. Modelling of soil erosion and deposition patterns using the MODERN model to calculate the depth of soil loss/gain. [ABSTRACT FROM AUTHOR]

The flash flood-induced erosion is the primary contributor to soil loss within the Indian Himalayan Region (IHR). This phenomenon is exacerbated by a confluence of factors, including extreme precipitation events, undulating topographical features, and suboptimal soil and water conservation practices. Over the past few decades, several flash flood events have led to the significant degradation of pedosphere strata, which in turn has caused landslides along with fluvial sedimentation in the IHR. Researchers have advocated morphometric, hydrologic, and semi-empirical methods for assessing flash flood-induced soil erosion in hilly watersheds. This study critically examines these methods and their applicability in the Alaknanda River basin of the Indian Himalayan Region. The entire basin is delineated into 12 sub-watersheds, and 13 morphometric parameters are analyzed for each sub-watershed. Thereafter, the ranking of sub-watersheds vulnerability is assigned using the Principal Component Analysis (PCA), compounding method (CM), Geomorphological Instantaneous Unit Hydrograph (GIUH), and Revised Universal Soil Loss Equations (RUSLE) approaches. While the CM method uses all 13 parameters, the PCA approach suggests that the first four principal components are the most important ones, accounting for approximately 89.7% of the total variance observed within the dataset. The GIUH approach highlights the hydrological response of the catchment, incorporating dynamic velocity and instantaneous peak magnifying the flash flood susceptibility, lag time, and the time to peak for each sub-watershed. The RUSLE approach incorporates mathematical equations for estimating annual soil loss utilizing rainfall-runoff erosivity, soil erodibility, topographic, cover management, and supporting practice factors. The variations in vulnerability rankings across various methods indicate that each method captures distinct aspects of the sub-watersheds. The decision-maker can use the weighted average to assign the overall vulnerability to each sub-watershed, aggregating the values from various methods. This study considers an equal weight to the morphometric, hydrological GIUH, and semi-empirical RUSLE techniques to assess the integrated ranking of various sub-watersheds. Vulnerability to flash flood-induced landslides in various sub-watersheds is categorized into three classes. Category I (high-priority) necessitates immediate erosion control measures and slope stabilization. Category II (moderate attention), where rainwater harvesting and sustainable agricultural practices are beneficial. Category III (regular monitoring) suggests periodic community-led soil assessments and afforestation. Sub-watersheds WS11, WS8, WS5, and WS12 are identified under category I, WS7, WS4, WS9, and WS6 under category II, and WS1, WS3, WS2, and WS10 under category III. The occurrence of landslides and flash-flood events and field observations validates the prioritization of sub-watersheds, indicating the need for targeted interventions and regular monitoring activities to mitigate environmental risks and safeguard surrounding ecosystems and communities. [ABSTRACT FROM AUTHOR]

Compacted soils are vital in constructing unpaved roads and embankments for infrastructure projects, requiring a thorough understanding of how different soil properties influence erosion. This research examined the influence of suction on the mass loss of clayey soil from the Guabirotuba Formation, compacted at various degrees of saturation and densities. The study involved initial physical–chemical, mineralogical, and morphological soil characterization. Tests were then conducted to determine the soil water characteristic curve, hydraulic conductivity, and erodibility using the filter paper method, permeability tests, and the Inderbitzen test. Samples were compacted to dry unit weights of 14.55 kN/m3, 15.42 kN/m3, and 16.28 kN/m3 with saturation levels of 20%, 50%, 91.08%, 93.49%, and 95.60%. Results showed that variations in soil density altered the soil water characteristic curve, tending towards a unimodal shape with reduced void ratios. Soil permeability decreased in the desaturation zone of the curve. The study determined that soil mass loss is primarily influenced by saturation degree and density, with saturation emerging as the most crucial factor. Erosion resistance was observed to be lowest at 50% saturation compared to both 20% and optimal saturation levels, which was associated with a reduction in the unsaturated permeability coefficient. It has been found that the influence of slope is negligible. Therefore, soil saturation levels significantly affect erosion resistance, making the soil more susceptible to disruption when air continuously occupies the pore space. [ABSTRACT FROM AUTHOR]

Robust soil ecosystems are crucial for sustaining life on our planet and enhancing agricultural output. Soil erosion poses a significant threat to the health of these ecosystems. Gully erosion is capable of breaking down the soil ecosystem and degrades the quality of water in rivers and wetlands. This study aims to map and predict gully erosion susceptibility zones in the Birbhum district of West Bengal, India, using advanced machine learning models and nature-inspired optimization techniques. It addresses the significant issue of gully erosion, which degrades soil ecosystems and water quality. Eight machine learning models, namely Random Forest (RF), glmnet, C5.0, eXtreme Gradient Boosting (XGB), model averaged neural network (avNnet), AdaBoost, gradient boosting machine (GBM), and multivariate adaptive regression splines (MARS) algorithms were employed to map the susceptible zone for gully erosion with thirty-three conditioning parameters in the study area. Each of the main and sub factors were suitability ranked and weighted with the FuzzyAHP evaluation for integration with ML model. The parameters were selected through the novel nature inspired wrapper algorithms (Particle Swarm Optimization (PSO), Genetic Optimization (GO), Grey Wolf Optimization (GWO), Harris Hawk Optimization (HHO), and Dragon Fly Optimization (DFO)) and evaluated through multi-collinearity test as well as Boruta sensitivity analysis. Based on the validating parameters, such as accuracy, kappa, sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and area under the receiver operating characteristic curve (AUROC) showed the RF, C5.0, XGB and AdaBoost models could be used for identifying susceptible gully erosion zones following 10-fold resampling technique. In terms of AUC, the RF, XGB and GBM models showed sound performance (> 0.92) along with good accuracy level (> 0.80). According to the Boruta sensitivity analysis, the top four parameter's namely elevation, distance to river, sand, and river density were the most influential factors. The severity of gully erosion was identified in the western and central zones of the study area having denser water bodies and comparatively higher run off depth. CMIP6 MIROC6 and EC-Earth3 climate data for ssp245 and ssp585 scenarios were also used for predicting future (2023–2060) gully erosion expansion trend in the study area for 10-fold resampling rate through the best performing ML models. The concerning situation of gully erosion in the study area required instant and promising steps to prevent soil losses through gully erosions promised to achieve the sustainable development goal (SDGs). [ABSTRACT FROM AUTHOR]

Soil erosion inventory of a river basin is vital for effective soil conservation and sustainable development considering the ongoing Global change. In the current study, gross soil erosion rates (A) are estimated for a mountainous river in a tropical climate, the Karamana River Basin (KRB), southern India by utilizing the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model computes 'A', as a product function of five variables; rainfall erosivity (R), soil erodibility (K), topographic factor (LS), crop management factor (C), and erosion control practice factor (P). To compute these five parameters, the digital elevation model, slope, normalized vegetation index (NDVI), rainfall and land use/land cover (LULC) are used along with the texture data of soil samples collected from KRB. The estimated A values range between 0 to 738.44 t ha−1 year−1, with an average of 10.22 t ha−1 year−1 whereas the sediment yield (SY) estimated by utilizing the sediment delivery ratio (SDR) model ranges between 0 to 246.68 t ha−1 year−1 with an average of 1.58 t ha−1 year−1 for KRB. For further validation, a soil erosion potential index (SEPI) map is developed to identify the soil erosion-prone zones of KRB using the geo-environmental thematic maps following the analytic hierarchy process (AHP). Finally, rainfall impacts on soil erosion are evaluated and quantified for KRB, considering the recent marked variations in rainfall that are induced by the extreme climatic events (cyclones/high rainfall/floods) along the West coast of India. The outcome of this study suggests that increasing rainfall by one standard deviation of the long-term average causes a significant increase in low and medium soil erosion regions. [ABSTRACT FROM AUTHOR]

The increase in pore water pressure, directly associated with the compressibility of loose sands under seismic loading, induces liquefaction, resulting in a decrease in effective stresses and, consequently, a loss of soil strength and stiffness in saturated sandy soils. For a long time, geotechnical engineers have found it difficult to understand the phenomenon of soil liquefaction. It is crucial to look into the factors influencing the liquefaction and/or softening of soil as well as the production and evolution of pore water pressure to have a deeper knowledge of the liquefaction phenomena. The size of the particles is one of the important factors. The purpose of this work is to examine how sand particle size, repetitive loading, and undrained circumstances affect the development of excessive pore water pressure. SEM and EDX imaging were conducted to determine the characteristics of three different sands. To ascertain the parameters of shear resistance, three sands with varying gradations were chosen and subjected to direct shear tests. For each of the three sands with varying particle sizes, cylindrical triaxial test specimens were made, and a set of dynamic triaxial tests under stress control were performed. The specimens were tested at various repeated stress ratios (CSR) using loading frequency of 0.1 Hz after being isotropically consolidated under an effective stress of 100 kPa. Experiments on three different sands with varying grain sizes and shapes revealed increased liquefaction potential with a reduction in grain diameter. It was observed that as the cyclic shear strain increased, the sand samples reached liquefaction at lower cycles. Additionally, it was noted that incorporating empirical coefficients that consider grain size and shape into the prediction of pore water pressure improved compatibility with models commonly used in the literature, leading to better results. [ABSTRACT FROM AUTHOR]

According to reports, Ethiopia is one of the countries in sub-Saharan Africa with the worst affected by soil erosion. It has both on-site and off-site consequences on biophysical and socioeconomic settings in an area. The study area is heavily affected by soil erosion forming diverse erosion structures, particularly in the upper course of the watershed. Hence, this work seeks to estimate the geographically distributed annual soil loss rate and mapping of soil erosion hazard hotspot areas in the watershed using the Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions. The RUSLE parameters, such as rainfall erosion factor (R-factor), soil erodibility factor (K-factor), slope steepness and slope length factor (LS-factor), land cover factor (C-factor), and conservation practice factor (P-factor) were considered as data input for the analysis to quantify the soil loss rate in the study area. A digital elevation model (DEM) with a 12.5 × 12.5-meter resolution was employed for catchment delineation and determination of the LS factor.The mean yearly rainfall data from the surrounding rain gauge stations was used to analyze the R-factor. The results of the current conditions showed that the average typical soil loss rate from the entire watershed is 23.8 t ha-1 yr-1, and the quantity of soil loss from the study area ranged from 0 to 776.71tan /ha-1 yr-1. Nonetheless, Tiro Afeta experiences mean soil erosion at a rate of roughly 50.2 t ha-1 yr-1, exceeding the acceptable threshold of 11 t ha-1 yr-1. Determining the sustainability of soil production requires assessment, particularly in cases where significant yearly soil erosion occurs. Due to intensive agricultural activities in the Xiro Afeta watershed, significant soil erosion is predominantly occurring in thissteep upper region. Consequently, this area urgently requires appropriate soil protection measures. [ABSTRACT FROM AUTHOR]

Numerous hydrological applications, such as soil erosion estimation, water resource management, and rain driven damage assessment, demand accurate and reliable rainfall erosivity data. However, the scarcity of gauge rainfall records and the inherent uncertainty in satellite and reanalysis-based rainfall datasets limit rainfall erosivity assessment globally. Here, we present a new global rainfall erosivity dataset (0.1° × 0.1° spatial resolution) integrating satellite (CMORPH and IMERG) and reanalysis (ERA5-Land) derived rainfall erosivity estimates with gauge rainfall erosivity observations collected from approximately 6,200 locations across the globe. We used a machine learning-based Gaussian Process Regression (GPR) model to assimilate multi-source rainfall erosivity estimates alongside geoclimatic covariates to prepare a unified high-resolution mean annual rainfall erosivity product. It has been shown that the proposed rainfall erosivity product performs well during cross-validation with gauge records and inter-comparison with the existing global rainfall erosivity datasets. Furthermore, this dataset offers a new global rainfall erosivity perspective, addressing the limitations of existing datasets and facilitating large-scale hydrological modelling and soil erosion assessments. [ABSTRACT FROM AUTHOR]

Meghalaya is known for its complex environment due to its hilly terrain and heavy rains, which result in significant soil erosion challenges. The LS factor is the primary factor used to estimate soil loss. Acquiring accurate LS values has always been a significant challenge. The main aim of this research is to compute the LS factor in the Meghalaya region. Three methods are used to calculate the LS factor: (1) Wischmeier and Smith's (1978) method, (2) Moore and Wilson's (1992) method, and (3) Desmet and Gover's (1996) method. All three approaches used the digital elevation model (DEM) in the spatial domain to determine the LS factor. The results of this investigation demonstrated significant variation in LS factor in all three methods. Wischmeier and Smith's method yielded LS factor values ranging from 0 to 266.538, Moore and Wilson's method resulted in values ranging from 0 to 112.631, and Desmet and Gover's method resulted in values ranging from 0 to 683.679. This study concluded that Wischmeier and Smith's method resulted in LS factor values distributed uniformly across the spatial domain. In contrast, Moore and Wilson's method only yielded high values along the flow path and low values in other areas. Additionally, Desmet and Gover's method identified high LS factors in regions with steep slopes near rivers and streamlines. This study can be helpful in anticipating soil erosion well before time and also in developing a slope management plan in the study region. [ABSTRACT FROM AUTHOR]

The lack of soil erosion data and other information about watersheds continues to limit soil erosion modeling. To overcome these limitations, many researchers have turned to machine learning models to analyze and model the complex water erosion processes and integrate them with empirical models. The Beni Haroun dam watershed faces soil erosion due to specific geo-environmental settings and land practices. It poses serious threats to agricultural and natural resource development. For these reasons, this study attempts to identify soil erosion susceptible zones using the Revised Universal Soil Loss Equation (RUSLE) using five key factors (rainfall erosivity, soil erodibility, topography, cover management and conservation practice factor) in GIS environment. Furthermore, we integrated the five RUSLE parameters and the model outputs into two machine learning (ML) algorithms, namely Random Forest (RF) and Random Tree (RT). The proposed models underwent training on 70% of the dataset and were subsequently validated on the remaining 30%. Our results indicated that the most vulnerable to severe soil erosion was concentrated in northwest regions, in contrast to the southeastern regions, which most occupy low erosion and moderate erosion. RUSLE and RT-based RUSLE models yielded nearly identical results in classifying erosion severity, estimating the annual average soil erosion at 17.5 and 17.69 (t ha–1y–1), respectively. In contrast, the Random Forest RF-based RUSLE model presented slightly divergent findings 23.89 (t ha–1y–1). Overall, these findings contribute to the identification of the area's most vulnerable to soil erosion, providing valuable insights to inform land management and conservation strategies. [ABSTRACT FROM AUTHOR]