Search

Enhancing terrestrial carbon (C) stock through ecological restoration, one of the prominent approaches for natural climate solutions, is conventionally considered to be achieved through an ecological pathway, i.e., increased plant C uptake. By conducting a comprehensive regional survey of 4279 1 × 1 m² plots at 517 sites across China's drylands and a 13-y manipulative experiment in a semiarid grassland within the same region, we show that greater soil and ecosystem C stocks in restored than degraded lands result predominantly from decreased surface soil C loss via suppressed wind erosion. This biophysical pathway is always overlooked in model evaluation of land-based C mitigation strategies. Surprisingly, stimulated plant growth plays a minor role in regulating C stocks under ecological restoration. In addition, the overall enhancement of C stocks in the restored lands increases with both initial degradation intensity and restoration duration. At the national scale, the rate of soil C accumulation (7.87 Tg C y-1) due to reduced wind erosion and surface soil C loss under dryland restoration is equal to 38.8% of afforestation and 56.2% of forest protection in China. Incorporating this unique but largely missed biophysical C-conserving mechanism into land surface models will greatly improve global assessments of the potential of land restoration for mitigating climate change. [ABSTRACT FROM AUTHOR]

Past nuclear weapons testing (NWT) and nuclear power plant (NPP) accidents have resulted in the ubiquitous deposition of radionuclides in the environment. While radionuclide contamination of the environment is associated with concerning health risks, these fallout radionuclides (FRNs) are considered the privileged markers ("golden spikes") of the Anthropocene stratigraphic layers. Their deposition in the 1950s coincided with the "Great Acceleration", which is characterized by large-scale shifts in the Earth's systems, including increased land-use change and soil degradation. Among the FRNs deposited globally, 137Cs has been the most commonly used to assess soil erosion and/or the chronology of sediment deposition, and 239+240Pu is an emerging soil erosion tracer and chronological marker increasingly used due to a number of advantages. We compiled 137Cs and 239+240Pu data published from undisturbed (so called "reference") soils in the Equatorial and Southern Hemisphere regions to build a database under the AVATAR Project ("A reVised dATing framework for quantifying geomorphological processes during the Anthropocene"). Using this database, named the AVATAR-Soils Database, we determined the distributions of 137Cs and 239+240Pu inventories in Equatorial and Southern Hemisphere soils, along with the relative contributions of different fallout nuclear weapon sources by analysing their isotopic ratios. Additionally, we demonstrated how the database can be used to identify the environmental factors that influence the distributions of 137Cs and 239+240Pu in reference soils by applying a machine-learning algorithm. Our metanalysis revealed that high 137Cs and 239+240Pu inventories were recorded near the equator and within the 20–40° S latitudinal bands, which coincide with the location of multiple NWT. The 240Pu/239Pu atomic ratios suggest that sources other than the global fallout (primarily from US and USSR weapon testing with a 240Pu/239Pu atomic ratio of ~ 0.18) contributed to the reference inventories in the Southern Hemisphere. These additional sources have been relatively neglected so far. On average, the French fallout contributed ~20 % to the reference soil 239+240Pu inventories in South America and up to 70 % in French Polynesia. In contrast, the British fallout contributed ~27 % to the reference soil 239+240Pu inventories in the rest of Oceania. Our machine-learning algorithm identified precipitation of the coldest quarter, longitude, and latitude as the strongest predictors of 137Cs inventory. For 239+240Pu inventory, mean diurnal temperature range, temperature annual range, and precipitation of the driest quarter were the strongest predictors. Altogether, these findings demonstrate the potential of the AVATAR-Soils Database as resource for improving our understanding of the distribution and sources of 137Cs and 239+240Pu in Equatorial and Southern Hemisphere soils and refining their application as tools in various Earth Science research. The AVATAR-Soils Database may be accessed at https://doi.org/10.5281/zenodo.14008220 (Dicen et al., 2024). [ABSTRACT FROM AUTHOR]

Soil erosion is a major environmental problem with detrimental consequences. In this article, we present a detailed study on the analysis of soil water erosion using machine learning (ML) techniques in the Oued Ourika watershed in Morocco. We collected data on various factors that may influence the mechanisms of soil water erosion events. Subsequently, we developed machine learning models to predict the potential for soil water erosion based on these factors. Finally, field studies were conducted compared to the obtained results. A historical inventory of water erosion has been created through fieldwork, satellite imagery, and historical water erosion events. Models were constructed using the training data, and their performance and accuracy in predicting susceptibility to water erosion were evaluated using the validation data. This data division allowed for a fair assessment of the models’ ability to make accurate predictions. Using a Geographic Information System (GIS) and programming in the R language, four supervised machine learning algorithms were applied, including k-nearest neighbor (KNN), extreme gradient boosting (XGB), random forest (RF), and naive bayes (NB). The results show that the NB model exhibited the highest accuracy in predicting and evaluating the effectiveness of these algorithms in forecasting susceptibility to water erosion in the study area. Accuracy was assessed using the area under the curve (AUC) metric, with an AUC of 98%. The XGB algorithm had an AUC of 96%, followed by RF with an AUC of 87%, and KNN with an AUC of 84%. Thus, the Naive Bayes model proved to be the best for determining susceptibility to water erosion in the study area. The analysis of water erosion reveals that 43% of the total area of the Oued Ourika watershed is exposed to a high to very high risk of erosion in the Ourika region. These findings can assist regional and local authorities in reducing the risk of water erosion and implementing effective measures to prevent potential damages. The goal is to protect the communities and infrastructure located along the course of the Ourika. Overall analysis of natural disasters, the accuracy of the results heavily depends on the availability and quality of data, which must encompass an adequate number of parameters. [ABSTRACT FROM AUTHOR]

Mercury (Hg) is a persistent pollutant highly bioaccumulated in the aquatic environment through the food chain reaching high concentration levels in the tissues of predator fishes. Among the relevant sources of anthropogenic mercury emissions in Latin America and the Caribbean (LAC), mining is one of the most important along with soil erosion due to deforestation and agricultural activities where pesticides are intensively used. Several reports have demonstrated an association between a fish-based diet with elevated Hg levels in the blood and neurotoxic effects in humans. In this systematic review with quantitative analysis data from 92 articles were compiled, providing evidence of Hg concentration in fishes that are commonly consumed in LAC. An assessment was conducted using three indices for health risk: the Minamata Initial Assessment (MIA), the Target Hazard Quotient (THQ), and the Meals per Week (MPW) index. Of the 410 fish species studied, 5.4% had concentrations above 0.95 μg g−1 of wet weight (ww), which is the recommended limit for Total Hg (THg) ingestion through fish consumption according to the MIA index, regardless of the water habitat (i.e., marine or freshwater). Additionally, the Target Hazard Quotient (THQ) calculation indicated high-risk values (THQ ≥ 1) in 15 out of the 19 countries studied, and very high-risk values (THQ ≥ 10) were obtained from Hg concentrations measured in 5 fish species inhabiting watersheds in Trinidad and Tobago, Suriname and Peru. Finally, recommendations on fish consumption were made based on the MPW index. This study reveals the need for updated biomonitoring studies of Hg concentrations in fish to perform more accurate human health risk analyses. [ABSTRACT FROM AUTHOR]

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]

It is well known within the dam engineering profession that the potential for earthquake-induced cracking is a key consideration in the design and construction of dams. Transverse cracking of embankment dams is a major concern of engineers involved in dam safety management and commonly represents a potential failure mode for such dams. If transverse cracking extends below the reservoir level, it may lead to leakage from the reservoir, internal erosion of the embankment soils, and dam failure. Considerable effort has been made in the engineering profession during the last few decades to study the nature and effects of dam earthquake cracking and to develop design measures to mitigate its potential occurrence. However, few studies exist on earthquake-induced cracking of embankment dams, and the profession's ability to accurately predict its characteristics is limited. Thus, it seems useful to review key aspects of earthquake cracking of embankment dams and some of the lessons learned about cracking from the past performance of dams during earthquakes. This paper aims to fulfill this objective by providing an overview of the observed effects of earthquakes on embankment dams, discussing the potential for embankment dam failure by cracking, reviewing basic concepts about the mechanics of cracking in soils, discussing the analysis of embankment dam cracking in practice, and presenting two case histories of cracking of embankment dams. The case histories describe (1) the performance of Matahina dam during construction, reservoir filling, and the 1987 Edgecumbe earthquake in New Zealand and (2) the performance of Lenihan dam during the 1989 Loma Prieta earthquake in California and an analysis of the dam for that earthquake. [ABSTRACT FROM AUTHOR]

The original stress equilibrium state of the soil is destroyed after the excavation of the double-line shield tunnel, resulting in the settlement of the stratum above the tunnel and bringing adverse effects on the surface buildings and subsurface pipelines near the tunnel. The reasonable prediction of subsurface settlement is significant for protecting adjacent underground structures. The wave propagation model is introduced to describe the settlement mechanism of the stratum above the tunnel based on random medium theory, and the subsurface settlement model of single-line tunnel is derived through the Fourier transform. The disturbance influence factor of double-line tunnel is defined, and the corresponding settlement model is established. The three-dimensional subsurface settlement models of single-line and double-line shield tunnels are proposed by introducing the surface displacement release rate of palm surface and maximum slope of surface vertical settlement. The models are verified using monitoring data, and the effects of the parameters on the model are analyzed. [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]

Gravel soil faces significant engineering challenges such as leakage erosion and soil flow due to its complex composition and susceptibility to groundwater effects. This study integrates the entire machine learning process, including pre- and post-processing of images, WGAN implementation, and validation of hydraulic and morphological properties. Obtaining intact gravel soil samples is difficult and costly due to their erodible nature in the Li River, China. A μ-CT scanning series is employed to capture detailed images with three microstructural characteristics of gravel soil, forming the basis for training datasets using WGANs. This approach allows the generation of similar 3D realizations that replicate the microstructural characteristics and hydraulic behaviors of a prototype of gravel soils. Through computational fluid dynamics (CFD) simulations, the effectiveness of the realizations in hydraulic behavior within reconstructed porous structures is verified. This process indirectly validates the consistency between the realization′s microstructure and the prototype. This integrated methodology not only enhances understanding but also aids in the optimization of engineering designs and applications in geotechnical and materials science disciplines. [ABSTRACT FROM AUTHOR]

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

Gully erosion is a significant natural hazard and a form of soil erosion. This research aims to predict gully formation in the Kalshour basin, Sabzevar, Iran. Employing the Information Gain Ratio (IGR) index, we identified 13 key factors out of 22 for modeling, with elevation emerging as the most influential factor in gully formation. The study evaluated the performance of individual machine learning algorithms and ensemble algorithms, including the Functional Tree (FT) as the main classifier, Bagging (Bagg), AdaBoost (Ada), Rotation Forest (RoF), and Random Subspace (RSS). Using a data set of 400 gully and non‐gully points obtained through field investigations (70% for training and 30% for testing), the RoF model achieved an area under the curev (AUC) value of 0.99, indicating its high predictive ability for gully‐susceptible areas. Other algorithms also performed well (Ada: 0.90, FT: 0.92, RSS: 0.94, Bagg: 0.95). However, the RoF algorithm with the functional tree as the main classifier (RoF_FT) demonstrated the highest ability in gully classification and susceptibility mapping, enhancing the functional tree's performance. In addition to AUC, the RoF_FT model achieved an F1 score of 0.89 and an MCC of 0.78 on the validation set, indicating a high balance between precision and recall, and a strong correlation between predicted and actual classes, respectively. Similarly, other models showed robust performance with high F1 scores and MCC values, but the RoF_FT model consistently outperformed them, underscoring its robustness and reliability. The resulting gully erosion‐susceptibility map can be valuable for decision‐makers and local managers in soil conservation and minimizing damages. Implementing proactive measures based on these findings can contribute to sustainable land management practices in the Kalshour basin. RecommendationsGully erosion threat: Gully erosion poses a significant threat to soil, with far‐reaching environmental consequences.Predictive modeling: This research focuses on predicting gully formation in the Kalshour basin, Sabzevar, Iran, using advanced machine learning algorithms.Key findings for decision‐makers: The study evaluates the performance of various machine learning algorithms and ensemble algorithms, with the Functional Tree serving as the main classifier. This not only enhances our ability to predict gully formation but also provides a valuable tool for decision‐makers and local managers in soil conservation.Impact on sustainable land management: By offering a gully erosion‐susceptibility map, the research empowers decision‐makers to implement proactive measures, minimizing damage and contributing to sustainable land management practices.Interdisciplinary approach: The study's combination of geospatial analysis, machine learning, and soil conservation aligns with the journal's mission to advance understanding in environmental modeling. [ABSTRACT FROM AUTHOR]

The article "Correction to 'Object-Based Image Analysis (OBIA)-based gully erosion dynamics, sediment loading rate and sediment yield study in Lake Hawassa Subbasin, Ethiopia'" discusses the significant environmental issue of gully erosion in the Lake Hawassa Subbasin. The study aims to map and analyze changes in gully erosion, quantify sediment loading rates, and determine sediment yields using Object Based Image Analysis (OBIA) with high-resolution satellite images. The results show a rapid increase in gully extent between 2011 and 2020, impacting 5.53% of the subbasin area and leading to significant sediment loading into the lake. The study highlights the importance of addressing gully erosion to prevent further siltation and loss of the lake's storage capacity. [Extracted from the article]

Dams are vital for irrigation, power generation, and domestic water needs, but siltation poses a significant challenge, especially in areas prone to water erosion, potentially shortening a dam's lifespan. The Ahmed El Hansali Dam in Morocco faces heightened siltation due to its upstream region being susceptible to erosion-prone rocks and high runoff. This study estimates the siltation at the dam from its construction up to 2014 using bathymetric data and the Brown model, which is a widely-used empirical model that calculates reservoir trap efficiency. Additionally, the study evaluates the impact of Land Use and Land Cover (LULC) changes and projected future rainfall until around 2076 based on siltation rates. The results indicate that changes in LULC, particularly temporal variations in precipitation, have a significant impact on the siltation of the Ahmed El Hansali dam. Notably, rainfall is strongly correlated with the siltation rate, with an R2 of 0.92. The efficiency of sediment trapping (TE) is 97.64%, meaning that 97.64% of the sediment in the catchment area is trapped or deposited at the bottom of the dam. The estimated annual specific sediment yield is about 32,345.79 tons/km2/yr, and the sediment accumulation rate is approximately 4.75 Mm3/yr. The dam's half-life is estimated to be around 2076, but future precipitation projections may extend this timeframe due to the strong correlation between siltation and precipitation. Additionally, soil erosion driven by land management practices plays a crucial role in future siltation dynamics. Hence, this study offers a comprehensive assessment of the siltation dynamics at the Ahmed El Hansali dam, providing essential information on the long-term effects of erosion, land use changes, and climate projections. These findings may assist decision makers in managing dam reservoir sedimentation more effectively, ensuring the durability of the dam and extending the reservoir life. [ABSTRACT FROM AUTHOR]

Soil erosion is both the cause and effect of land degradation. Land use/land cover conversion that changes the inherent landscape structure of watersheds leads to soil loss increase. Pantabangan-Carranglan Watershed (PCW) as a major source of irrigation, electricity, biodiversity, livelihood, and other ecosystem services, thus, it is imperative to spatially and temporally estimate the soil erosion within its boundary to assist and guide decision-makers in planning conservation and management of the watershed. Using the Revised Universal Soil Loss Equation (RUSLE) model, remotely sensed data, soil analysis, and geographical information system, the soil erosion rate in PCW was estimated. Results showed that there is increasing soil erosion in PCW over time. In 2010 soil erosion rate was estimated to be 134 tons·ha-1·yr-1 which increased to 141 tons·ha-1·yr-1 and 154 tons·ha-1·yr-1 in 2015 and 2020, respectively. Considering the average soil erosion rate and land cover types in PCW, annual crop and open/barren land cover types have the highest average soil erosion rate through time with moderate and catastrophic erosion levels, respectively. [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]

Scrub root systems play a crucial role in preventing soil erosion and nutrient loss. However, the effects of the root system configuration on soil nutrient dynamics and microbial changes at various evolutionary stages remain poorly understood. In this study, we investigated the relationship between soil physical and chemical properties and the diversity of bacteria and fungi throughout the evolutionary stages of the scrub root systems. This was achieved through a combination of whole-root excavation and root tracing techniques. The results indicated that root diameter was the main factor contributing to the continuous increase in carbon (C): phosphorus (P) and nitrogen (N): P ratios as the scrub sand pile developed. The soil organic carbon (SOC), total soil nitrogen (TN), and total soil phosphorus (TP) contents in the soil in the four evolutionary stages were the highest during the developmental stage, but the change in TP content was not statistically significant (P > 0.05). Partial least squares path modeling and redundancy analysis (RDA) indicated that root system stoichiometric C and N contents were positively correlated with microbial diversity (R² = 0.85). There was no correlation between the evolutionary stage and soil nutrient TN, whereas soil nutrient TN was negatively correlated with microbial diversity (R² = −0.92). These findings elucidate the relationship between the evolutionary stage of root chemical measurement characteristics, soil elements and microorganisms, and their subsequent effects on root elemental composition and microbial diversity. This study enhances the current understanding of plant–soil interactions in desert steppe ecosystems. [ABSTRACT FROM AUTHOR]

The current issue affecting land and water resources is soil erosion. Its numerous detrimental effects include deforestation, unfavorable farming methods, and decreased fertility, all of which impede socioeconomic growth. This research aimed to evaluate the effects of land use land cover (LULC) dynamics on soil erosion and its spatial distribution patterns over the Hare Watershed for the periods 2001–2021. Revised Universal Soil Loss Equation (RUSLE) model coupled with a geographic information system (GIS) was applied to estimate potential soil losses; this involved utilizing data on rainfall erosivity (R) using interpolating rainfall data, topography (LS) using digital elevation model (DEM), soil erodibility (K) using the William equation and digital soil map, conservation practices (P) using DEM and satellite images, and vegetation cover (C) using satellite images. To account for the change in LULC over the past 20 years, three separate maps of C‐factors were developed for the years 2001, 2011, and 2021. The remaining four factors were kept constant. Finally, after the successful running of the model, the estimated annual average soil loss rate (A) of the watershed is 211.38, 223.79, and 235.64 t·ha−1yr−1 for the years 2001, 2011, and 2021, respectively. This is a result of grazing areas and shrubland being lost for agricultural land. Moreover, in the past period, the watershed was found to show an increase in the yearly mean soil loss rate of 24.26 t·ha−1yr−1. Consequently, the northeastern, northwest, and southern regions of the watershed require the implementation of suitable land management. [ABSTRACT FROM AUTHOR]

Understanding the impact of climate and land use change on soil erosion is particularly important to the development and management of ecosystems. The purpose of this research was to differentiate the impacts of climate and land use alterations on soil erosion by using the InVEST model in the Anning River basin. The findings indicated a rise in average soil erosion from 42.78 t ha−1·a−1 to 49.84 t ha−1·a−1 over the decade from 2010 to 2020, with climate change accounting for 99.71% of the increase and land use change contributing 0.28%. The findings also indicated that the process of urbanization and the implementation of the Returning Grain to Forestry and Grass (RGFG) strategy were effective in decreasing soil erosion by 1.29 t ha−1·a−1 and 6.60 t ha−1·a−1, respectively. Four management measures were developed based on our results. The results of this study are not only of great significance for the environmental protection of a specific region, but also provide references for the mitigation of soil erosion in other regions of the world. [ABSTRACT FROM AUTHOR]

Rammed earth, a commonly used building material in ancient times, differs from natural sedimentary layers in that it is more compact. Buildings constructed from historical rammed earth sites frequently encounter the issue of rainwater erosion. Microbially induced calcium carbonate precipitation (MICP) is commonly applied to sand soil treatment, yet reports on its use for stabilizing rammed earth are scarce. This study focused on the rammed earth of the Shanhaiguan Great Wall and explored the efficacy of MICP in mitigating rain erosion through permeation tests, splash experiments, and scouring trials. The findings indicate that the forms of rain erosion damage under MICP treatment vary across different operational conditions. In laboratory experiments, as the concentration of the cementation solution increases, the amount of calcium carbonate crystals also increases. However, the permeability, splash resistance, and rain erosion resistance initially increase and then decrease. When the cementation solution concentration is 1.0 mol/L, the penetration rate is the highest, lasting 712.55 s. The splash pit rate is the lowest, at only 1.2 mm, and the soil erosion rate is the lowest, at only 4.13%. The rain erosion resistance in the field test exhibit the same trend, and the optimal concentration is 1.2 mol/L. The optimal concentration mechanism involves the aggregation of calcium carbonate crystals at suitable cementation solution concentrations, which begin to fill the soil particle pores, effectively resisting rainwater erosion. At lower concentrations of the cementation solution, calcium carbonate crystals are merely adsorbed by soil particles without blocking the pores. Due to the high compressibility of rammed earth, which results in lower porosity, a higher concentration of the cementation solution leads to rapid pore clogging by excessive calcium carbonate crystals, which accumulate on the surface to form a white crust layer. The MICP technique can effectively alleviate rainwater erosion in rammed earth, and the optimal concentration needs to be tailored to the porosity of the rammed earth. This mechanism was also validated in field scouring experiments on the Shanhaiguan Great Wall's rammed earth. [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]

The black soil region experiences complex erosion due to natural processes and intense human activities, leading to soil degradation and adverse ecological and agricultural impacts. However, the complexities involved in quantifying regional erosion poses remarkable challenges in accurately assessing the current status of regional soil erosion for effective soil conservation. To solve this issue, we proposed a new method for monitoring soil erosion using Interferometric synthetic aperture radar (InSAR) technology and machine learning algorithms within the Google Earth Engine platform. The new method not only enables regional-scale monitoring, but also ensures high accuracy in measurement (millimeter-level). The erosion susceptibility of the study area (Yanshou County, Heilongjiang Province, Northeastern China) was also classified using random forest algorithms to refine the monitored and predicted soil erosion. The results indicate that the five-year (2016–2021) deformation in Yanshou County was −11.08 mm, with a significant mean cumulative deformation of −8.08 mm yr−1 occurring in 2017. The driving factor analysis shows that the region was subject to the compound effect of water and freeze–thaw erosion, closely related to crop phenological stages. The susceptibility analysis indicates that 73.3% of the region was susceptible to erosion, with a higher probability in river areas, at high altitudes, and on steep slopes. However, good vegetation cover can reduce the risk of soil erosion to some extent. This study offers a new perspective on monitoring regional soil erosion in the black soil region of China. The proposed method holds potential for future expansion to monitor soil erosion in a larger areas, thereby guiding the strategies development for protection of the agriculturally important black soil. [ABSTRACT FROM AUTHOR]

Forest carbon stock is an important indicator reflecting a forest ecosystem's structures and functions. Its spatial distribution is valuable for managing natural resources, protecting ecosystems and biodiversity, and further promoting sustainability, but accurately mapping the forest carbon stock distribution in a large area is a challenging task. This study selected Changting County, Fujian Province, as a case study to explore a method to map the forest carbon stock distribution using the integration of airborne Lidar, Sentinel-2, and ancillary data in 2022. The Bayesian hierarchical modeling approach was used to estimate the local forest carbon stock based on airborne Lidar data and field measurements, and then the random forest approach was used to develop a regional forest carbon stock estimation model based on the Sentinel-2 and ancillary data. The results indicated that the Lidar-based carbon stock distribution effectively provided sample plots with good spatial representativeness for modeling regional carbon stock with a coefficient of determination (R2) of 0.7 and root mean square error (RMSE) of 12.94 t/ha. The average carbon stocks were 48.55 t/ha, 55.51 t/ha, and 57.04 t/ha for Masson pine, Chinese fir, and broadleaf forests, respectively. The carbon stock in non-conservation regions was 15.2–16.1 t/ha higher than that in conservation regions. This study provides a promising method through the use of airborne Lidar data as a linkage between sample plots and Sentinel-2 data to map the regional carbon stock distribution in those subtropical regions where serious soil erosion has led to a relatively sparse forest canopy density. The results are valuable for local government to make scientific decisions for promoting ecosystem restoration due to water and soil erosion. [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]

A one-dimensional numerical overland flow model based on the cascade plane theory was developed to estimate rainfall-induced runoff and soil erosion on converging and diverging plane surfaces. The model includes three components: (i) soil infiltration using Horton's infiltration equation, (ii) overland flow using the kinematic wave approximation of the one-dimensional Saint-Venant shallow water equations for a cascade of planes, and (iii) soil erosion based on the sediment transport continuity equation. The model's performance was evaluated by comparing numerical results with laboratory data from experiments using a rainfall simulator and a soil flume. Four independent experiments were conducted on converging and diverging surfaces under varying slope and rainfall conditions. Overall, the numerically simulated hydrographs and sediment graphs closely matched the laboratory results, showing the efficiency of the model for the tested controlled laboratory conditions. The model was then used to numerically explore the impact of different plane soil surface geometries on runoff and soil loss. Seven geometries were studied: one rectangular, three diverging, and three converging. A constant soil surface area, the rainfall intensity, and the slope gradient were maintained in all simulations. Results showed that increasing convergence angles led to a higher peak and total soil loss, while decreasing divergence angles reduced them. [ABSTRACT FROM AUTHOR]

The terrain in the loess hilly area of western Henan is fragmented, with steep slopes and weak soil erosion resistance. The substantial soil erosion in this region results in plenty of problems, including decreased soil productivity and ecological degradation. These problems significantly hinder the social and economic development in the region. Soil conservation planning and ecological development require accurate soil erosion surveys. However, the studies of spatio-temporal patterns, evolution, and the driving force of soil erosion in this region are insufficient. Therefore, based on a multi-stage, unequal probability, systematic area sampling method and field investigation, the soil erosion of the loess hilly area of western Henan was quantitatively evaluated by the Chinese Soil Loss Equation (CSLE) in 2022. The impact forces of soil erosion were analyzed by means of a geographic detector and multiple linear regression analysis, and the key driving factors of the spatio-temporal evolution of soil erosion in this region were revealed. The results were as follows. (1) The average soil erosion rate of the loess hilly area in western Henan in 2022 was 5.94 t⋅ha−1⋅a−1, with a percentage of soil erosion area of 29.10%. (2) High soil erosion rates mainly appeared in the west of Shangjie, Xingyang, and Jiyuan, which are related to the development of production and construction projects in these areas. The areas with a high percentage of soil erosion area were in the north (Xinan and Yima), west (Lushi), and southeast (Songxian and Ruyang) of the study area. Moreover, areas with the most erosion were found in forest land, cultivated land, and areas with a slope above 25°. (3) At the landscape level, the number and density of patches of all land types, except orchard land, increased significantly, and the boundary perimeter, landscape pattern segmentation, and degree of fragmentation increased. (4) The geographical detector and multiple linear regression analysis indicated that the driving forces of soil erosion are mainly topographic and climatic (slope length, elevation, precipitation, and temperature). Soil erosion was significantly influenced by the density of landscape patches. These maps and factors influencing soil erosion can serve as valuable sources of information for regional soil conservation plans and ecological environment improvements. [ABSTRACT FROM AUTHOR]

Soil erosion is a global environmental problem, and soil conservation is the prevention of soil loss from erosion. The Ten Kongduis (kongdui is the translation of "short-term flood gullies" in Mongolian) are ten tributaries in the upper Inner Mongolia section of the Yellow River Basin. The study of the spatial and temporal variability in soil conservation in the Ten Kongduis is of extraordinary scientific significance both in terms of the discipline and for the ecological and environmental management of the region. With the InVEST model, the characteristics of the spatial and temporal variations in soil conservation service in the Ten Kongduis since 2000 and how rainfall and land use have influenced soil conservation were analyzed. The results show that both avoided erosion and avoided export varied considerably between years. The minimum values of avoided erosion and avoided export were both in 2015, with values of 17.59 × 106 t and 0.92 × 106 t, respectively. The maximum value of avoided erosion was 57.03 × 106 t in 2020 and that of avoided export was 4.08 × 106 t in 2000. Spatially, avoided export was primarily found in the upper reaches of the east–central portion of the study area, and avoided erosion, with values of >40 t·(ha·yr)−1, was in the upper east–central portion of the study area, followed by the upper west–central portion. The difference between upstream and downstream was larger in the western part of the study area. The effect of rainfall was dominant and positive in both avoided erosion and avoided export. The relationships between the rain erosivity factor and the values of avoided erosion and avoided export were significantly positive. Where more erosion occurs, more erosion is retained. Soil that has been eroded away from slopes under vegetation or other water conservation measures may not necessarily be transported to the stream channel in the current year. These conclusions will help us to have a clearer understanding of where sediments are generated and transported and provide a scientific basis for soil and water conservation and ecosystem safety management of watersheds. [ABSTRACT FROM AUTHOR]

This study investigated the impact of thinning and felled logs (random- and contour-felled logs) on overland flow, soil erosion, and litter erosion in a Japanese cypress forest plantation (2400 tree ha−1) with low ground cover, from 2018 to 2023 in central Japan. Monthly measurements of overland flow and soil and litter erosion were carried out using small-sized traps across three plots (two treatments and one control). In early 2020, a 40% thinning (tree ha−1) was conducted in the two treatment plots. Overland flow increased in the plot with random-felled logs during the first year post-thinning (from 139.1 to 422.0 L m−1), while it remained stable in the plot with contour-felled logs (from 341.8 to 337.1 L m−1). A paired-plot analysis showed no change in overland flow in the contour-felled logs plot compared to the control plot from the pre- to post-thinning periods (pre-thinning Y = 0.41X − 0.69, post-thinning Y = 0.5X + 5.46, ANCOVA: p > 0.05). However, exposure to direct rainfall on uncovered ground areas post-thinning led to increased soil and litter erosion in both treatment plots. These findings suggest that thinning combined with contour-felled logs effectively stabilizes overland flow. Therefore, thinning with contour-felled logs can be considered a viable method for mitigating overland flow in monoculture plantations with low ground cover. [ABSTRACT FROM AUTHOR]

[Objective] To investigate the response mechanism of temporal and spatial distribution of soil organic carbon (SOC) loss to soil erosion intensity, in order to provide basic data for the study of soil carbon cycling mechanism under erosion environment, and provide scientific basis for solving the problem of "thinning and thinning of black soil. Methods］ This study selected 1 4 cities (districts or counties) such as Bei,an, Keshan, Kedong and Baiquan counties in the typical black soil area of Songnen Plain as the research objects, and employed the RUSLE model in conjunction with the spatial analysis techniques of GTS to explore the characteristics of temporal and spatial variations in soil erosion and SOC loss in the typical black soil region of Northeast China from 2000 to 201 9. Results］ Soil erosion intensity in the study area exhibits a high-north and low-south distribution pattern, predominantly characterized by slight erosion. From 2000 to 2()19，the proportion of slight erosion area in typical black soil area showed a inapparent upward trend, while the proportion of slight erosion area and above showed a decreasing trend. Notably, 87.91% of the area did not undergo significant changes in the degree of erosion intensity, with only 3.74% of the are experiencing an escalation in erosion severity. SOC loss exhibited significant spatial distribution differences, generally following a high-north and low-south distribution pattern, with an average annual loss intensity of SOC at 4.74 t/(km2 • a). From 2010 to 2()19，the total SOC loss showed an increasing trend, with the highest loss occurring in Bei'an，accounting for 37.0()% of the total loss in the study area. Between 2()15 and 201 9, the proportion of areas with soil organic carbon loss intensity less than 5 t/(km2 • a) has decreased, while the proportion of areas with loss intensity greater than 5 t/(kniJ • a) has increased, leading to an increase in the annual average loss intensity. Tn the northern part of the study area, where soil erosion intensity is high, the abundant SOC content resulted in relatively larger total organic carbon loss upon erosion, giving rise to a distinct regional variation in SOC loss totals. _Conclusion] The temporal and spatial characteristics of SOC loss under the action of erosion, indicating that severe soil erosion is an important driving factor of SOC loss on slope. [ABSTRACT FROM AUTHOR]

[Objective] To scientifically identify the types of soil erosion at the watershed scale and give the corresponding probability of occurrence. Methods］ This study constructs a deep learning (T)L) 一based model for calculating soil erosion modulus in the Songhua River Basin and calculates different types of soil erosion modulus. Using three erosion modulus influencing factors? namely rainfall, air temperature and wind speed, as random variables, numerical simulation and Gaussian Kernel Density Estimation (GKDE) were used to construct the EM probability evaluation method, which gives the probability of occurrence of different combinations of soil erosion intensities. Results］ The R' of the validation period of the EM computational models were all >0.86； 74.47% of the average annual occurrence of slight water erosion and slight wind erosion in the watershed; 12.86% of the area of slight and above water erosion and slight wind erosion ； 12.56% of the area of slight and above wind erosion and slight water erosion； ().11% of the area of water erosion strength and wind erosion intensity are both slight and above. 36 typical image elements of the 36 typical images, the average probability of occurrence of slight water erosion and slight wind erosion is 57.45%； the average probability of occurrence of slight water erosion and mild wind erosion is 30.26%; the average probability of occurrence of slight water erosion and moderate wind erosion is &()3%; the average probability of occurrence of mild water erosion and slight wind erosion is 2.11 % ； the average probability of occurrence of slight water erosion and severe wind erosion is 2.()8% ； and the evaluations of occurrence of the remaining combinations of probabilities were all below ().05%. Conclusion] The calculation model of erosion modulus in the Songhua River basin constructed in this study has high accuracy, reveals the spatial distribution characteristics of soil erosion types in the Songhua River basin, and gives the probability of occurrence of different combinations of the intensity of the two types of erosion, which provides a basis for the management of soil erosion in the Songhua River basin. [ABSTRACT FROM AUTHOR]

[Objective Kuye River Basin is the main source of erosion in the coarse sand area in the middle reaches of the Yellow River. The study is aimed at elucidating the spatio-temporal pattern of soil erosion. predicting the development trend of soil erosion in Kuye River Basin and providing decision support for the comprehensive control of soil erosion in the future. [Methods] Based on the multi-source data from 2010 to 2020, the spatial distribution of soil erosion in the Kuye River Basin was studied, and the characteristics of soil erosion intensity change were analyzed by using quantitative indicators such as dynamic degree of soil erosion intensity, I information entropy of soil erosion intensity, comprehensive index of soil erosion intensity and transfer matrix. The CA-Markov model was established to predict the soil erosion in 2025. [Results] (1) The soil erosion intensity in the study area was mainly in micro and mild erosion, accounting for more than 70% of the total area, and stronger erosion was mainly distributed in the middle and lower reaches of the basin and tributary Beiniuchuan. From 2010 to 2020, the average soil erosion decreased from 1 955.56 t/(km². a) to 892.98 t/(km² a), the area of micro erosion increased significantly, and the area of other erosion intensity decreased correspondingly. The soil erosion intensity remained unchanged or decreased in most regions> and only less than 3% of the regions experienced increased erosion intensity. (2) The dynamic degree of intensity, extreme intensity and extreme erosion in Kuye River Basin changed greatly, the information entropy of soil erosion intensity decreased steadily from 1.29 to 0.81, the comprehensive index of soil erosion intensity decreased from 178.96 to 76.61 and the decline rate was higher in the first five years. and the change of soil erosion intensity in the basin to the weakening direction mainly occurred between the two adjacent erosion intensity levels. (3) CA-Markov model simulation shows that, it is expected that by 2025. the soil erosion situation in the basin will be further improved, with the proportion of micro erosion accounted more than 75%..Conclusion] From 201 0 to 2020. the soil erosion situation in the study area continued to improve. and the control efficiency of soil erosion in the next five years was higher. and the soil erosion situation in the basin would be further improved in 2025. [ABSTRACT FROM AUTHOR]

The enhancement of soil erosion resistance via soil and water conservation practices is a necessary venture in the modern agricultural industry. Soil infiltration performance, as a necessary indicator of erosion resistance, is closely related to soil aggregates. However, the relationship between the C/N ratio of soil aggregates and soil infiltration and the overall performance under conservation tillage practices is unclear. Experiments were conducted in 2022 and 2023 to observe the relationship between the soil carbon and nitrogen distribution patterns and soil infiltration of sloping cultivated land under different tillage practices. In this study, ridge tillage and pitting field + subsoiling tillage (RF-S) and contour tillage + subsoiling tillage (TP-S) have been used in a plot experiment, with down-slope cultivation (CK) as the control. The results showed that the stability of soil aggregates, the organic carbon and the total nitrogen contents of soil aggregates of different particle-sizes, and the overall soil infiltration performance were greatly increased under the RF-S and TP-S treatments (up-slope, mid-slope, and down-slope). Compared with CK, RF-S and TP-S significantly improved the stability of soil aggregates at different slope positions (on, in, and under the slope) and the C/N ratio and soil infiltration performance of aggregates with particle sizes of >2 mm and 2–0.25 mm. However, TP-S more effectively reduced the deposition of soil macroaggregates down the slope and can comprehensively improve the stability of soil aggregates and the infiltration performance. The mean weight diameter (MWD) and mean geometric mean diameter (GMD) of soil aggregates can reflect the distribution and stability of soil aggregates and also indicate the stability of soil structure. Compared with CK, the MWD of TP-S soil aggregates increased by 6% to 17.7%, the GMD increased by 9.7% to 27.2%, the average soil infiltration rate increased by 41.8% to 78.3%, the initial infiltration rate increased by 19.1% to 46.6%, and the stable infiltration rate increased by 109.2% to 165.9%. Soil infiltration performance is positively correlated with the C/N ratio of aggregates with particle sizes of >2 mm and 2–0.25 mm and negatively correlated with the C/N ratio of aggregates with particle sizes of <0.25 mm. The results of this study show that reasonable tillage measures are helpful in improving soil water and soil conservation and anti-erosion ability and illustrate the influence mechanism of soil aggregates on soil infiltration performance. [ABSTRACT FROM AUTHOR]

Solar energy plays a major role in the transition to renewable energy. To ensure that large-scale photovoltaic (PV) power plants operate at their full potential, their monitoring is essential. It is common practice to utilize drones equipped with infrared thermography (IRT) cameras to detect defects in modules, as the latter can lead to deviating thermal behavior. However, IRT images can also show temperature hot-spots caused by inhomogeneous soiling on the module's surface. Hence, the method does not differentiate between defective and soiled modules, which may cause false identification and economic and resource loss when replacing soiled but intact modules. To avoid this, we propose to detect spatially inhomogeneous soiling losses and model temperature variations explained by soiling. The spatially resolved soiling information can be obtained, for example, using aerial images captured with ordinary RGB cameras during drone flights. This paper presents an electrothermal model that translates the spatially resolved soiling losses of PV modules into temperature maps. By comparing such temperature maps with IRT images, it can be determined whether the module is soiled or defective. The proposed solution consists of an electrical model and a thermal model which influence each other. The electrical model of Bishop is used which is based on the single-diode model and replicates the power output or consumption of each cell, whereas the thermal model calculates the individual cell temperatures. Both models consider the given soiling and weather conditions. The developed model is capable of calculating the module temperature for a variety of different weather conditions. Furthermore, the model is capable of predicting which soiling pattern can cause critical hot-spots. [ABSTRACT FROM AUTHOR]

Land use and cover change (LUCC) is directly linked to the sustainability of ecosystems and the long-term well-being of human society. The Helong Region in the Loess Plateau has become one of the areas most severely affected by soil and water erosion in China due to its unique geographical location and ecological environment. The long-term construction of terraces and orchards is one of the important measures for this region to combat soil erosion. Despite the important role that terraces and orchards play in this region, current studies on their extraction and understanding remain limited. For this reason, this study designed a land use classification system, including terraces and orchards, to reveal the patterns of LUCC and the effectiveness of ecological restoration projects in the area. Based on this system, this study utilized the Random Forest classification algorithm to create an annual land use and cover (LUC) dataset for the Helong Region that covers eight periods from 1986 to 2020, with a spatial resolution of 30 m. The validation results showed that the maps achieved an average overall accuracy of 87.54% and an average Kappa coefficient of 76.94%. This demonstrates the feasibility of the proposed design and land coverage mapping method in the study area. This study found that, from 1986 to 2020, there was a continuous increase in forest and grassland areas, a significant reduction in cropland and bare land areas, and a notable rise in impervious surface areas. We emphasized that the continuous growth of terraces and orchards was an important LUCC trend in the region. This growth was primarily attributed to the conversion of grasslands, croplands, and forests. This transformation not only reduced soil erosion but also enhanced economic efficiency. The products and insights provided in this study help us better understand the complexities of ecological recovery and land management. [ABSTRACT FROM AUTHOR]

Evaluation ecosystem service value (ESV) is critical, as "lucid waters and lush mountains are invaluable assets". To assess the incremental effects of ecological assets on soil and water conservation in subtropical mountains, we developed a remote-sensing-driven mountainous equivalent factor (RS-MEF) method to estimate the ESV of Changting County, China. This method is a hybrid of a conventional equivalent factor framework and remote sensing techniques for mountains, achieving several advancements, including spatial adjustment using vegetation activity merged with productivity, improved spatial resolution, and the removal of topographic effects. Using the RS-MEF method, we estimated that the ESV of Changting County was approximately CNY 15.80 billion in 2010 and CNY 34.83 billion in 2022. Specifically, the ESV per unit area of the major soil erosion area (MSEA) in the county was less than that of the non-major soil erosion area (n-MSEA); however, the ESV growth rate of the MSEA from 2010 to 2022 was faster than that of the n-MSEA. Therefore, the ESV gap between the two areas was reduced from 28.99% in 2010 to 15.83% in 2022. Topographic gradient analysis illustrates that areas with elevations of 385 to 658 m and steep slopes achieved a high ESV, while high-elevation areas with gentle slopes will be a focus of control in the next phase. Our study demonstrates that significant achievements have been made in ecological restoration from an ESV perspective, with a notable reduction in low-ESV areas in the MSEA; the insights gained into ESV growth and its underlying factors are valuable and instructive for future soil and water conservation efforts. [ABSTRACT FROM AUTHOR]

Fractional vegetation cover (FVC) is an essential metric for valuating ecosystem health and soil erosion. Traditional ground-measuring methods are inadequate for large-scale FVC monitoring, while remote sensing-based estimation approaches face issues such as spatial scale discrepancies between ground truth data and image pixels, as well as limited sample representativeness. This study proposes a method for FVC estimation integrating uncrewed aerial vehicle (UAV) and satellite imagery using machine learning (ML) models. First, we assess the vegetation extraction performance of three classification methods (OBIA-RF, threshold, and K-means) under UAV imagery. The optimal method is then selected for binary classification and aggregated to generate high-accuracy FVC reference data matching the spatial resolutions of different satellite images. Subsequently, we construct FVC estimation models using four ML algorithms (KNN, MLP, RF, and XGBoost) and utilize the SHapley Additive exPlanation (SHAP) method to assess the impact of spectral features and vegetation indices (VIs) on model predictions. Finally, the best model is used to map FVC in the study region. Our results indicate that the OBIA-RF method effectively extract vegetation information from UAV images, achieving an average precision and recall of 0.906 and 0.929, respectively. This method effectively generates high-accuracy FVC reference data. With the improvement in the spatial resolution of satellite images, the variability of FVC data decreases and spatial continuity increases. The RF model outperforms others in FVC estimation at 10 m and 20 m resolutions, with R2 values of 0.827 and 0.929, respectively. Conversely, the XGBoost model achieves the highest accuracy at a 30 m resolution, with an R2 of 0.847. This study also found that FVC was significantly related to a number of satellite image VIs (including red edge and near-infrared bands), and this correlation was enhanced in coarser resolution images. The method proposed in this study effectively addresses the shortcomings of conventional FVC estimation methods, improves the accuracy of FVC monitoring in soil erosion areas, and serves as a reference for large-scale ecological environment monitoring using UAV technology. [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]

[Objective The aims of this study are to analyze the response of farmland surface runoff and sediment loss to rainfall patterns under different planting modes, to explore the laws of farmland surface runoff and sediment transport in the Poyang Lake plain area under new circumstances, and to provide scientific basis for preventing and controlling farmland surface soil erosion, [Methods] 64 rainfall events were classified using K-means clustering method, and combined with monitoring data such as runoff and sediment production in runoff plots, the impact of surface runoff and sediment losses in different rainfall types of farmlands under three planting modes were analyzed. Results] (1) The duration, rainfall and maximum rainfall intensity of 30 minutes were taken as the rainfall characteristic indicators. The rainfall could be divided into 4 types (type A: 'medium duration, small rainfall and light rainfall intensity', type B: 'short duration, small rainfall and medium rainfall intensity', type C: 'long duration, heavy rainfall and medium rainfall intensity', and type D: short duration, medium rainfall and heavy rainfall intensity'). (2) The variation of runoff and rainfall of each planting mode was basically the same, and the runoff was also more when the rainfall was larger. In each month dry farming mode produced the most runoff, (3) No matter what type of rainfall, the runoff and sediment losses of dry farming mode were the highest. Under the types A and C. the runoff and sediment yields of water farming mode were the lowest. Under the type B. the runoff reduction effect of water and dry rotation mode was the best. (4) There were significant differences in the total runoff and sediment loss under different planting modes, and the performance followed the order: dry farming mode paddy upland rotation mode paddy farming mode. [Conclusion In conclusion. compared with the dry farming model, the water farming model has certain advantages in reducing runoff and sediment, especially when dealing with type A and type C. the effect of runoff and sediment reduction is more obvious. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to investigate the changing rates of runoff and sediment reduction capacity for long-term forest and grass vegetation coverage plots, and to provide a scientific basis for vegetation restoration of soil and water conservation in southwest rocky mountain area of China. [Methods] From 2018 to 2021, the data of runoff and sediment yield, vegetation coverage as well as soil surface water content in the five runoff plots. i.e. 15° bare land, 15° grassland, 15° forest land, 30° forest land and 30° grassland, were observed in Tiantai Town, Chishui City, Guizhou Province. The changes of runoff coefficient and sediment concentration were used to reflect the changing rates of runoff and sediment reduction capacity in each plot. [Results] The order of flow and sediment reduction benefits in the five communities was 30° grassland 15° forest > 30° forest 15° grassland bare land. Among them, the vegetation coverage of the 30° grassland community was the highest, at 92.8%, with runoff and soil erosion modulus of 2.43 mm and 6.51 t/(km² a), respectively. The bare land community had the highest runoff, at 153.49 mm, and the highest soil erosion modulus, at 1 214.5 t/(km² a). The runoff coefficient of the 15° grassland community decreased the fastest at 0.292%/a, and its sediment content also decreased the fastest at-14.6 g/(La). There was a significant negative correlation between vegetation coverage and runoff, a significant negative correlation with sediment concentration, and a significant positive correlation with soil surface water content. [Conclusion] High vegetation coverage is beneficial for vegetation restoration, water conservation, and soil erosion control. For the 15° grassland slope with relatively severe soil erosion, the long-term vegetation coverage has a more significant effect on soil and water conservation. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to determine the spatial distribution of water erosion and its spatial-temporal variation in southwest alpine-canyon area, to explore driving mechanism of water erosion in study area, and to provide countermeasures for regional soil erosion and water loss control. [Methods] Based on GIS and RUSLE model, the spatial and temporal variation and driving mechanism of water erosion in southwest alpine-canyon area were analyzed by using the method of the Theil-Sen trend analysis. Mann- Kendall significance test and random forest model. [Results (1) The ratio of light erosion and mild erosion was over 78.05%. (2) Generally, during the period of 2000 to 2020, the range of water erosion amount varied between 4.606 3×108 t and 1.487 4×109 t and the annual value was 7.9664×108t. The range of rainfall erosion factor amount varied between 125.11 MJ mm/(hm².h.a) and 249,93 MJ mm/(hm² ha) and the annual value was 186.71 MJ mm/(hm²h.a). The range of vegetation coverage and management factor varied between 0.37 and 0.70 and the average value for years was 0.48. (3) Topographic factors was with the highest contribution to explain spatial variation of water erosion, accounting for 41%, followed by vegetation coverage and management factors, rainfall erosion factor, soil erodibility factor, soil and water conservation measure factor, accounting for 24%, 16%, 12%, and 8%, respectively. Moreover, spatial variation contribution of each factor varied with the soil and water conservation zone. [Conclusion] The severe erosion areas mainly distributed in the southern part of Eastern Xizang & West Sichuan Ecological Maintenance & Water Conservation Region. Eastern and northwest part of Southeast Xizang arctic-alpine Ecological Maintenance Region. Topographic factors and vegetation coverage and management factors was the main driving factors. In the Ecological Maintenance and Water Conservation Zone of Eastern Xizang & Western Sichuan, the Southeast Xizang Ecological Maintenance Arctic alpine Zone and the Northwest Yunnan Ecological Maintenance Zone, the measures that would improve the vegetation cover to increase the soil anti-erodibility was suggested. In the North Yunnan & Southwest Sichuan Water Storage and Soil Conservation Zone, vegetation cover should be improved while appropriate soil and water conservation measures could be placed. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to assess the accuracy of soil erodibility K calculated by different methods in the key soil loss areas of Anhui Province, and to refine each calculation method based on the measured erodibility K. [Methods] The Nomo equation, modified Nomo equation, EPIC model, DG model and Torri model were utilized to estimate the soil erodibility K values. Based on monitoring data from runoff plots in Huoshan County, Guangde County, Yuexi County and She County, the actual erodibility factor K values were obtained to evaluate the effectiveness of each method. [Results] The soil erodibility K values in Huoshan County, Guangde County, Yuexi County and She County were 0.033~0.035, 0.018, 0.021 and 0.041 (thm² h)/(hm² MJ mm), respectively. The differences in soil erodibility K values derived from different methods were significant, with all methods greatly overestimating the K values. The overall ranking of the methods in terms of soil erodibility followed the order: K Torri> K Noma> KM-Nomo >K DG> K Epic. The methods of calculating K values for each were improved, in which the improved Nomo equation and the modified Nomo equation showed superior performance. [Conclusion] The improved Nomo equation and modified Nomo equation are recommended to apply in the key soil loss areas of Anhui Province. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to investigate the sediment sources of slope erosion in production and construction projects, and to implement the targeted soil and water conservation measures to mitigate soil and water loss caused by human disturbance. [Methods] Indoor simulated rainfall tests combined with REE tracer technique were conducted to examine the erosion characteristics and contributions from different areas of engineering deposits with varying gravel contents [0 (pure soil), 10%, 20%, 30%] under the rainfall intensity of 90 mm/h. [Results (1) The amount of soil erosion of all areas of different gravel-containing engineering deposits was the largest in the down slope area, while the average erosion contribution of the down slope area (57.40%) was larger than that of the upper slope area and the middle slope area, which indicated that the down slope area was the main source of sediment. (2) The erosion contribution of the middle and down slope areas of the gravel-containing engineering deposits was significantly smaller than that of the pure soil deposits. The erosion contribution of the upper and middle slope areas of the gravel-containing engineering deposits was significantly greater than that of the pure soil deposits, and the erosion contribution of the down slope area of the gravel-containing engineering deposits was significantly less than that of the pure soil deposits. (3) The effect of gravel content on the amount and contribution of erosion at the down slope area was more significant (p<0.05). In the gravel-containing engineering deposits, the amount of erosion at the upper and down slope areas of the 20% gravel content engineering deposits was significantly greater than that of engineering deposits with 10% and 30% gravel contents. The contribution of erosion at the upper slope area of the engineering deposit with 10% gravel content was significantly greater than that engineering deposits with 20% and 30% gravel contents, and the contribution of erosion at the down slope area was significantly less than that engineering deposits with 20% and 30% gravel contents. [Conclusion] Among all the engineering deposits with gravel content, the erosion contribution rate of the down slope area is the largest, which indicates that the down slope area is the main source of sediment on the slope of the engineering deposits, and the protection and treatment of the down slope area should be strengthened. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the characteristics and disparities in shear strength of root-soil complexes in different forest stands, and to provide a theoretical basis for addressing local soil erosion issues more effectively. [Methods] This study focuses on Beichuan County, Sichuan Province. Direct shear tests were conducted on intact root-soil complexes of several typical forest stands in the area, measuring relevant indicators such as shear strength, soil properties, and root characteristics. Principal component analysis was utilized to analyze the influencing factors of shear strength. [Results] (1) There were significant differences in shear strength among root-soil composites of different forest stands. The shear strength of 30-year-old Magnolia liliiflora forest (XY) was the highest, followed by Spotted bamboo Phyllostachys bambusoides forest (BZ), while the shear strength of 5-year-old Cryptomeria forest was the lowest. (2) The plant root system significantly contributed to soil stabilization, with an increase in shear strength of root-soil composites ranging from 0.13 kPa to 0.99 kPa, with an average increase of 350.0%. Additionally, the peak displacement, softening segment length, and residual shear strength of root-soil composites were enhanced, with average increases of 75.0%, 66.7%, and 262.5%, respectively. The total energy consumption of root-soil composites varied among different forest types but generally correlated with their shear strength. (3) Comprehensive analysis through principal component analysis revealed that, apart from soil bulk density and the dry and wet weights of 5~8 mm roots, all other indicators were closely related to shear strength. [Conclusion] Plant roots play a significant role in soil stabilization. The notable differences in shear strength of root-soil complexes were observed among different forest stands. [ABSTRACT FROM AUTHOR]

[Objective] Soil erosion caused by compound forces is obvious in Mollisol region, studying the annual alternating superposition of natural driving factors for soil composite erosion in different typical intervals in Northeast Mollisol Region has practical significance for soil erosion control in the region. [Methods] We analyzed and compared the spatiotemporal distribution of natural driving factors of water, wind, freeze-thaw, and snowmelt in 11 typical regions of the region, and clarified the alterative and superposition characteristics of each factor. [Results] In terms of time, the driving factors of hydraulic power, wind power, freeze-thaw and snowmelt in northeast Mollisol region occurred in superposition and alternation within the year. In spring, the driving factors of wind power, freeze-thaw and snowmelt were the most complex. In Summer, the driving factors of hydraulic power, wind power and freeze-thaw were the main driving factors. In autumn, the combined effects of hydraulic power, wind power and freezing and thawing were limited, while in winter, the effects of wind power and freezing were obvious. In terms of space, the hydraulic driving effect gradually decreased from southeast to northwest. Wind effect gradually decreased from southwest to northeast. The freeze-thaw effect gradually decreased from southwest to northeast. Snowmelt gradually decreased from northwest to southeast. According to the different characteristics of erosion driving factors, the whole region was divided into hydraulic, water-wind-freeze- thaw, water-wind-snow melt, water-freeze-thaw-snow melt erosion zones, and targeted soil erosion control could be carried out in different regions. [Conclusion] Each camp showed obvious temporal and spatial differences in their erosion performance. The characteristics of the composite erosion driving factors in a year were obtained based on the alternating superposition of natural driving factors within a year, providing reference for targeted soil erosion control and in-depth research on the composite erosion prevention and control in different regions. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the influence of slope, rainfall pattern and sugarcane growth period on soil erosion and nutrient loss on slope surface, and to provide theoretical basis for the mechanism improvement and prevention of soil erosion in sugarcane planting area of lateritic soil. [Methods] In-situ observation method in runoff area was used to explore the characteristics of soil erosion and loss of nitrogen nutrients (nitrate nitrogen and ammonium nitrogen) at different slopes (5° and 10°) under different rain types and sugarcane growth period. [Results] (1) The runoff in each growth period decreased in the order; extension period tillering periodseedling period mature period, and the nitrogen loss in tillering period was significantly higher than that in the other three periods (2.6~905.2 times). The sediment yield and their nitrogen nutrient loss followed the order: tillering stage extension period seedling period maturity period, the sediment yield of sugarcane in the tillering stage was significantly higher than that in other periods (2.9~71.4 times), and the difference was more obvious under the 10° slope. (2) Type B (medium rainfall depth, short duration, strong rainfall intensity) and type C (great rainfall depth, short duration, extremely strong rainfall intensity) were the main rainfall pattern that caused soil erosion and the nitrogen nutrient loss in sugarcane in the research area, contributing more than 70% of the slope runoff, sediment yield and nitrogen loss. In different slope treatments, there were significant differences in the sediment amount under type C, sediment ammonium nitrogen loss under type A and runoff ammonium loss under type B. (3) Rain pattern and sugarcane growth period had significant effects on runoff, sediment and those nitrogen loss on sugarcane slope (p<0.01), and the effect was higher than that of slope, interaction between slope and rain pattern, interaction between slope and growth period. Compared with runoff and those nitrogen loss, slope and its interaction with rain pattern and growth period showed more prominent effects on erosion sediment and nitrogen loss. [Conclusion] The slope had a more significant influence on the sediment and nitrogen nutrient loss process of sugarcane slope. The soil erosion and nitrogen nutrient loss were greatest in the tillering period, mainly contributed by type B and type C. [ABSTRACT FROM AUTHOR]

Gully erosion poses a threat to the sustainability of cultivated regions worldwide, is environmentally problematic, and causes significant rates of soil erosion. Understanding the formation process and gully development requires mapping gully erosion. An innovative modeling approach was used in this work using a case study in northern Iran. 14 gully-erosion parameter measurements from 1042 gully erosion locations were combined to produce a geographic dataset. For the purposes of modeling and validation, four training data sets (each in the standard 70:30 ratio) that represented 100 %, 75 %, 50 %, and 25 % of the total database were employed. The four machine learning models that were used to assess the utility of the four training situations were Bloom Filter Trees, Random Forest, (RF), Kernel Logistic Regression (KLR), and ensemble of KLR-RF. The most important effective factors, as determined by the RF research, were distance from the stream (72.61), vertical distance of the channel network (49.34), distance from the road (48.81), and elevation (47.68). The findings were validated using the receiver operating characteristic. Based on our findings, the combination of KLR and RF is the most optimum combination for both improved accuracy (0.928) and predictive capability (0.911). Out of them, the KLR-RF 50 % training scenario is the most optimal when compared to the other scenarios. [ABSTRACT FROM AUTHOR]

Soil erosion forms a serious ecological challenge to future production and sustainability, with implications of the environmental crisis and the food supply. It is one of the more critical geomorphological problems that threaten environmental sustainability and cause soil degradation along the Syrian coast. The object of this research is to evaluate the rate of probable annual water-induced soil erosion in the AL-Sanaoubar River Basin. By Integrating geographic information system (GIS), and remote sensing techniques with the Universal Soil Loss Equation (RUSLE). The results showed that the soil loss values in the AL-Sanaoubar River Basin ranged between 0–138.15 tons/ha/year, an average of 52.4 tons/ha/year. The total soil loss reached 12,606.11 tons/year for the entire studied area. The classification of possible spatial risk included five grades: very low (91.91%), low (7.62%), medium (0.35%), high (0.10%), and very high (0.01%). It has been noticed high soil erosion values in few portions of the study area, indicating that they had reached a risk stage; these sites were concentrated in the center and east of the studied basin, especially in the plateau and mountainous parts, Slope was a major factor that caused a direct impact on soil erosion. Soil erosion gradually increased with increasing slope in all types of land uses. To test the effectiveness of some soil conservation practices against water erosion, an experiment was conducted at the Mazar Qatrya site in Lattakia governorate during two consecutive seasons. Contour cultivation of the pea crop was applied at different distances, the agricultural method showed a high efficiency in reducing water erosion. Land use managers and Planners can benefit from this research to make suitable provisions and activities to conserve the soil. [ABSTRACT FROM AUTHOR]

Dispersive soil slopes are widely distributed in Northeast China. To analyze the failure caused by such slopes under various rainfall conditions, section K27 of the road-cutting slope of the Sui-Da Expressway in Heilongjiang Province, China, is considered an example. A 3D slope model was created using the similarity theory and visualized through close-range photogrammetry in a self-made model box. Six model tests were conducted under varying rainfall conditions to investigate the failure modes of dispersive soil slopes. Test results revealed that dispersive soil slopes are subject to two types of failure depending on the rainfall intensity. Slope erosion was divided into three stages by surface random roughness (SRR): initial erosion, constant velocity erosion, and accelerated erosion. Similarity theory suggests that the slope enters the accelerated erosion stage in the actual project when the SRR reaches around 31.95–46.5 cm. Furthermore, the reciprocal of the SRR change rate during the accelerated erosion stage exhibits a linear correlation with time. The time of the slope's complete failure can be estimated when the reciprocal of the SRR change rate is 0 min/cm. The research findings are significant for comprehending the failure process of dispersive soil slopes. [ABSTRACT FROM AUTHOR]

The escalating trend of land degradation poses a significant challenge, especially in sloping agricultural terrains, driven by the increasing global demand for food and the limited availability of flat arable land. In response to these challenges, farmers are compelled to shift their focus towards cultivating sloping terrains. This research aimed to employ a comprehensive methodology that integrates onsite field surveys, meticulous laboratory soil analyses, and geospatial data for mapping soil erodibility. The parameters under scrutiny encompass various crucial aspects, including soil texture (ranging from coarse sand to very fine sand, silt, and clay), soil structure, organic matter content, and permeability. The meticulous examination of these factors serves as the foundation for calculating soil erodibility, utilizing the well-established Wischmeir and Smith formula developed in 1978. The research findings present a nuanced understanding of soil erodibility in the study location, revealing a spectrum spanning low to very high erodibility. Specific units, such as Unit 1, Unit 2, Unit 3, Unit 7, Unit 9, Unit 10, Unit 13, and Unit 16, exhibit very low to low erodibility. In contrast, Unit 4, Unit 6, Unit 14, and Unit 15 showcase moderate erodibility, while units like Unit 5, Unit 8, Unit 11, Unit 12, Unit 17, and Unit 18 are characterized by moderately high to very high erodibility. These insightful results shed light on the diverse erodibility levels within the studied locations and provide valuable guidance for formulating sustainable land management practices. [ABSTRACT FROM AUTHOR]