Response of soil erosion resistance to straw incorporation amount in the black soil region of Northeast China.

Straw incorporation has been considered as an effective environmental management application to improve soil erosion resistance (SER) and organic carbon sequestration. SER is useful to evaluate soil erosion subjected to concentrated flow. Nevertheless, few studies have been performed to examine how SER varied with the amount of straw incorporation on sloping croplands in high latitude and cool regions. In the current study, the fixed bed scouring tests were conducted in a large hydraulic flume using undisturbed soil samples taken from Hebei small watershed in the black soil region of Northeast China. The response of SER to different straw incorporation amounts (0, 1.125, 2.25, 4.5, 6.75, 9.0 and 13.5 t ha-1) was quantified after three months of straw decomposition. The major influencing factors and the corresponding mechanisms were determined. The findings demonstrated that rill erodibility firstly decreased exponentially with straw incorporation amount (R2 = 0.93), while it slightly increased when straw incorporation amount was more than 9.0 t ha-1. Critical shear stress firstly increased logarithmically (R2 = 0.90) and then slightly decreased when the amount exceeded 9.0 t ha-1. Compared to the treatment of 0 t ha-1, rill erodibility reduced by 17.0%-92.8% and critical shear stress increased by 59.6%-127.2% across different treatments of straw incorporation. Rill erodibility had significant and negative correlations with soil organic matter content, aggregate stability, cohesion, root mass density, straw mass density and straw decomposition amount. The key mechanisms for promoting SER were derived by the direct and indirect effects of straw incorporation and its decomposition on soil physicochemical properties and crop roots. The amount of 9.0 t ha-1 was recommended as the optimum amount of straw incorporation in croplands in Northeast China. These findings are useful to understand how soil erosion resistance responds to the amount of straw incorporation and make rational environmental management policy for semi-humid and cool regions.

Sedimentary characteristics of ion-adsorption rare earth elements and assessment of their resource reuse potential due to soil and water erosion in western Fujian.

With severe soil and water erosion, the crucial ion-adsorption rare earth elements (REEs) have attracted much global attention. REEs play a vital role in tracing material sources and exploring sedimentary characteristics due to their unique and stable geochemistry properties. In the present work, three representational possible redeposition areas in western Fujian were selected as the study areas. The geochemical characteristics of REEs in the sediments of the study areas were evaluated to elucidate that REEs are the products of soil and water erosion and to assess their redeposition characteristics. In the research results, the properties of the parent rocks shown in the samples, together with the negative correlation between the content of REEs in the samples and altitude as well as the relief degree on the land surface (RDLS), fully indicate that the sediments in the study areas are the products of migration caused by soil erosion and redeposition in the downstream areas. At the same time, according to the widely applicable standard of rare earth resources exploitation, that is the boundary grade of ion-adsorption rare earth ore in southern China (∑REE = 500 mg·kg-1), we found that the content of REEs in the study areas was close to or exceeded this standard, and the maximum ∑REE of Guozhai Reservoir (869.11 mg·kg-1) was much larger than this standard. Therefore, the redeposited rare earth in Changting Country has high reuse potential under the current scarce resources.

Biological soil crust elicits microbial community and extracellular polymeric substances restructuring to reduce the soil erosion on tropical island, South China Sea.

Soil erosion stands as the preeminent environmental concern globally, attaining heightened significance, particularly within islands where land resources prove notably scarce. Biological soil crusts, referred to as biocrusts, assume a pivotal ecological role in soil conservation. Notably, they augment the horizontal stability of the substrate through the exudation of microbial extracellular polymeric substances (EPS), thereby shielding the soil against shear stress, exemplified in the form of water erosion. While extant research has delved into the anti-erosion mechanisms of biocrusts in arid landscapes, a conspicuous lacuna persists in the exploration of coral island environments. In this study, we collected and assessed 30 samples encompassing dark biocrusts, light biocrusts, and bare soil to scrutinize the potential anti-erosion efficacy of tropical coral island biocrusts within the South China Sea. Employing a cohesive strength meter, we quantified soil shear stress across various stages of biocrust development, revealing a discernible enhancement in soil erosion resistance during the formation of biocrusts. Relative to the exposed bare soil, the soil shear stress exhibited an escalation from 0.33 N m-2 to 0.61 N m-2 and 1.31 N m-2 in the light biocrusts and dark biocrusts, respectively. Mechanistically, we assayed microbial EPS contents, exposing a positive correlation between EPS and soil anti-erodibility, encompassing extracellular protein and polysaccharide. Concurrently, bacterial abundance displayed a significant augmentation commensurate with biocrust formation and development. In pursuit of elucidating the origin of EPS, high-throughput amplicon sequencing was executed to identify microorganisms contributing to biocrust development. Correlation analysis discerned Cyanobacteria, Chloroflexi, Deinococcota, and Patescibacteria as potential microbials fostering EPS production and fortifying erosion resistance. Collectively, our study presents the first evidence that biocrust from tropical coral reef island in the South China Sea promotes resistance to soil erosion, pinpointing key EPS-producing microbials against soil erosion. The findings would provide insights for island environment restoration.

Synthesis of soybean soluble polysaccharide-based eco-friendly emulsions for soil erosion prevention and control.

This paper introduces the synthesis of an environmentally friendly emulsion that can be used as a soil anti-water erosion material. SSPS-g-P(BA-co-MMA-co-AA) emulsions were prepared using free radical copolymerization with soybean soluble polysaccharide (SSPS), acrylic acid (AA), butyl acrylate (BA), and methyl methacrylate (MMA). The structure, thermal stability, and morphology were characterized using FT-IR,TG,SEM, and particle diameter analysis. The resistance to water erosion, compressive strength and water retention of emulsion-treated loess/laterite was studied and germination tests were conducted. The results demonstrated that the duration of washout resistance of loess with 0.50 wt% emulsion exceeded 99 h, and the water erosion rate was 56.0 % after 72 h, while the water erosion rate of pure loess is 100.0 % after 4 min;the duration of washout resistance of laterite with 0.50 wt% emulsion exceeded 2 h, which was 8 times longer than pure laterite;The compressive strengths of 0.5 wt% emulsion-treated loess/laterite were 3.5 Mpa and 5.8 MPa, respectively, which were 7 and 9 times higher than that of pure soil. The plant seeds germinated normally half a month after planting. These findings suggest that emulsions can be used to control soil erosion without affecting the germination of plant seeds.

Vascular plant communities and biocrusts act as controlling factors in mitigating soil erosion on the Great Wall in a semi-humid area of Northwestern China.

The Great Wall, a World Heritage Site and a vertical wall habitat, is under threat of soil erosion. The role of vascular plants and biocrust in controlling soil erosion has attracted attention, yet our knowledge of the underlying mechanism is limited, and there is a lack of systematic strategies for erosion prevention and control. In this study, we quantified the vascular plant community functional composition (including species diversity, functional diversity, and community-weighted mean), biocrust coverage, and soil erosion levels associated with seven different zones (lower, middle, and upper zones on East and West faces, plus wall crest) of the Great Wall. We then employed a combination of linear regression analysis, random forest model, and structural equation model to evaluate the individual and combined effects, as well as the direction and relative importance of these factors in reducing soil erosion. The results indicated that the vascular plant species richness, species diversity, functional richness, community-weighted mean, and moss crust coverage decreased significantly from the crest to the lower zone of the Great Wall (P < 0.05), and were negatively correlated with the soil erosion area and depth on both sides of the Great Wall (P < 0.05). This suggests that higher zones on the wall favored the colonization and growth of biocrusts and vascular plants and that biocrusts and vascular plants reduced soil erosion on the wall. Based on these findings, we propose a "restoration framework" for managing soil erosion on walls, based on biocrust and vascular plant communities (namely target species selection, plant community construction, biocrust inoculation, and maintenance of community stability), which aims to address the urgent need for more effective soil erosion prevention and control strategies on the Great Wall and provide practical methods that practitioners can utilize.

Impact of forest landscape restoration in combating soil erosion in the Lake Abaya catchment, Southern Ethiopia.

As an effect of forest degradation, soil erosion is among Ethiopia's most pressing environmental challenges and a major threat to food security where it could potentially compromise the ecosystem functions and services. As the effects of soil erosion intensify, the landscape's capacity to support ecosystem functions and services is compromised. Exploring the ecological implications of soil erosion is crucial. This study investigated the soil loss and land degradation in the Lake Abaya catchment to explore forest landscape restoration (FLR) implementation as a possible countermeasure to the effects. The study used a geographic information system (GIS)-based approach of the Revised Universal Soil Loss Equation (RUSLE) to determine the potential annual soil loss and develop an erosion risk map. Results show that 13% of the catchment, which accounts for approximately 110,000 ha, is under high erosion risk of exceeding the average annual tolerable soil loss of 10 t/ha/year. Allocation of land on steep slopes to crop production is the major reason for the calculated high erosion risk in the catchment. A scenario-based analysis was implemented following the slope-based land-use allocation proposal indicated in the Rural Land Use Proclamation 456/2005 of Ethiopia. The scenario analysis resulted in a reversal erosion effect whereby an estimated 3000 t/ha/year of soil loss in the catchment. Thus, FLR activities hold great potential for minimizing soil loss and contributing to supporting functioning and providing ecosystem services. Tree-based agroforestry systems are among the key FLR measures championed in highly degraded landscapes in Ethiopia. This study helps policymakers and FLR implementors identify erosion risk areas for future FLR activities. Thereby, it contributes to achieving the country's restoration commitment.

How the EU Soil Observatory contributes to a stronger soil erosion community.

New policy developments have emerged in relation to soil conservation after 2020. The Common Agricultural Policy (CAP) 2023-2027, the proposal for a Soil Monitoring Law and the mission 'A Soil Deal for Europe' have shaped a new policy framework at EU level, which requires updated assessments on soil erosion and land degradation. The EU Soil Observatory (EUSO) successfully organised a scientific workshop on 'Soil erosion for the EU' in June 2022. The event has seen the participation of more than 330 people from 63 countries, addressing important topics such as (i) management practices, (ii) large scale modelling, (iii) the importance of sediments in nutrient cycle, (vi) the role of landslides and (v) laying the foundations for early career scientists. As a follow up, among the 120 abstracts submitted in the workshop, we received fifteen manuscripts, out of which nine were selected for publication in the present special issue. In this editorial, we summarize the major challenges that the soil erosion research community faces in relation to supporting the increasing role of soils in the EU Green Deal.

Assessing soil erosion in a semiarid ecosystem in Central Argentina using 137Cs and 7Be measurements.

Argentina is a Latin American country which encounters soil degradation problems. The most productive regions have implemented conservative land practices (no-till). However, agricultural frontier has been displaced to marginal lands with arid and semiarid climates, with the consequent disappearance in many areas of native forest and land degradation. In this work, the fallout of gamma-emitting radionuclides, 137Cs and 7Be, was jointly used to assess changes in soil erosion in a recently converted semiarid ecosystem into agricultural land. 137Cs was utilized to estimate the erosion over the past 60 years, whereas 7Be was employed to estimate the erosion after the conversion of the area to cultivated land and soil tillage. For 137Cs the Proportional Model (PM), the Mass Balance Model II (MBMII) and the MODERN model were used, for 7Be the Profile Distribution Model (PDM) and the MODERN model were used. 137Cs indicates mean erosional rates of 8.2, 10.5 and 6.5 Mg ha-1 a-1, using MBMII, PM and MODERN, respectively, and that a soil layer between 0.5 and 0.8 mm was annually lost by erosion. By applying a 7Be tracer, we measured erosion rates of 2.4 and 3.3 Mg ha-1 (with PDM and Modern, respectively), indicating the loss of the upper 0.2 mm of soil. This erosion can be attributed to a few heavy rainfalls that occurred within the past 90 days. The results suggest that current land management practices have led to an increase in soil erosion. This could be attributed to the fact that the soil remains bare after crop harvest, which may compromise its conservation and future productivity.

Modelling of soil erosion susceptibility incorporating sediment connectivity and export at landscape scale using integrated machine learning, InVEST-SDR and Fragstats.

Evaluating the linkage between soil erosion and sediment connectivity for export assessment in different landscape patterns at catchment scale is valuable for optimization of soil and water conservation (SWC) practices. Present research attempts to identify the soil erosion susceptible (SES) sites in Kangsabati River Basin (KRB) using machine learning algorithm (decision trees, decision trees cross validation, CV, Extreme Gradient Boosting, XGB CV and bagging CV) taken thirty five variables, for investigating the linkage between erosion rates and sediment connectivity to assess the sediment export at sub-basin level employing connectivity index (IC) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) sediment delivery ratio (SDR) model. Based on AUC of receiving operating curve in validation test, excellent capacity of extreme Gradient Boosting, XGB CV and bagging CV (0.95, 0.90) than decision tree and decision tree CV (0.78, 0.82), exhibits about 18.58 % of basin areas facing susceptible to very high erosion. Conversely, considering universal soil loss equation (RUSLE) parameters, InVEST-SDR model estimated about 64.24 % of soil loss rate occurred from high SES in where sediment export rate become very high (136.995 t/ha-1/y-1). The IC result show that high sediment connectivity (<-4.4) measured in high SES of laterite and bare land in upper catchment, and double crop agricultural areas in lower catchment, while least connectivity (>-7.1) observed in low SES of dense forest, vegetation cover and settlement built-up areas. Pearson correlation matrix revealed that four landscape indices category i.e. edge metrics (p < 0.01), aggregation metrics (p < 0.001), shape metrics (p < 0.01-0.001) and diversity metrics (p < 0.01) signified the influence of landscape patterns on IC and SES. Accordingly, RUSLE, SDR and landscape matrices reveals that maximum sediment export rate associated with high connective delivery outlet and high SES in laterite, double crop and bare land due to simple landscape and greater homogeneity, whilst minimum export rate related with low connectivity and low SES in dense forest, vegetation cover and settlement built up area causes of fragmented landscape and spatial heterogeneity. Finally, findings could immense useful for formulating the optimizing measures of SWC in the watershed.

Top-predator recovery abates geomorphic decline of a coastal ecosystem.

The recovery of top predators is thought to have cascading effects on vegetated ecosystems and their geomorphology1,2, but the evidence for this remains correlational and intensely debated3,4. Here we combine observational and experimental data to reveal that recolonization of sea otters in a US estuary generates a trophic cascade that facilitates coastal wetland plant biomass and suppresses the erosion of marsh edges-a process that otherwise leads to the severe loss of habitats and ecosystem services5,6. Monitoring of the Elkhorn Slough estuary over several decades suggested top-down control in the system, because the erosion of salt marsh edges has generally slowed with increasing sea otter abundance, despite the consistently increasing physical stress in the system (that is, nutrient loading, sea-level rise and tidal scour7-9). Predator-exclusion experiments in five marsh creeks revealed that sea otters suppress the abundance of burrowing crabs, a top-down effect that cascades to both increase marsh edge strength and reduce marsh erosion. Multi-creek surveys comparing marsh creeks pre- and post-sea otter colonization confirmed the presence of an interaction between the keystone sea otter, burrowing crabs and marsh creeks, demonstrating the spatial generality of predator control of ecosystem edge processes: densities of burrowing crabs and edge erosion have declined markedly in creeks that have high levels of sea otter recolonization. These results show that trophic downgrading could be a strong but underappreciated contributor to the loss of coastal wetlands, and suggest that restoring top predators can help to re-establish geomorphic stability.

Improved soil carbon stock spatial prediction in a Mediterranean soil erosion site through robust machine learning techniques.

Soil serves as a reservoir for organic carbon stock, which indicates soil quality and fertility within the terrestrial ecosystem. Therefore, it is crucial to comprehend the spatial distribution of soil organic carbon stock (SOCS) and the factors influencing it to achieve sustainable practices and ensure soil health. Thus, the present study aimed to apply four machine learning (ML) models, namely, random forest (RF), k-nearest neighbors (kNN), support vector machine (SVM), and Cubist model tree (Cubist), to improve the prediction of SOCS in the Srou catchment located in the Upper Oum Er-Rbia watershed, Morocco. From an inventory of 120 sample points, 80% were used for training the model, with the remaining 20% set aside for model testing. Boruta's algorithm and the multicollinearity test identified only nine (9) factors as the controlling factors selected as input data for predicting SOCS. As a result, spatial distribution maps for SOCS were generated for all models, then compared, and further validated using statistical metrics. Among the models tested, the RF model exhibited the best performance (R2 = 0.76, RMSE = 0.52 Mg C/ha, NRMSE = 0.13, and MAE = 0.34 Mg C/ha), followed closely by the SVM model (R2 = 0.68, RMSE = 0.59 Mg C/ha, NRMSE = 0.15, and MAE = 0.34 Mg C/ha) and Cubist model (R2 = 0.64, RMSE = 0.63 Mg C/ha, NRMSE = 0.16, and MAE = 0.43 Mg C/ha), while the kNN model had the lowest performance (R2 = 0.31, RMSE = 0.94 Mg C/ha, NRMSE = 0.24, and MAE = 0.63 Mg C/ha). However, bulk density, pH, electrical conductivity, and calcium carbonate were the most important factors for spatially predicting SOCS in this semi-arid region. Hence, the methodology used in this study, which relies on ML algorithms, holds the potential for modeling and mapping SOCS and soil properties in comparable contexts elsewhere.

Bacterial carbonic anhydrase-induced carbonates mitigate soil erosion in biological soil crusts.

Soil erosion is a significant environmental issue worldwide, particularly in island regions where land resources are exceedingly scarce. Biological soil crusts play a crucial role in mitigating soil erosion, yet the precise effect and mechanism of biological soil crusts against erosion remain ambiguous. In this study, biological soil crusts at various developmental stages from a tropical coral island in the South China Sea were chosen to investigate the role of carbonic anhydrase in mitigating erosion. A cohesive strength meter, real-time quantitative PCR, and 16S rRNA gene high-throughput sequencing were employed to assess variations in soil antiscouribility as well as bacterial abundance and composition during the formation and development of biological soil crusts. Scanning electron microscopy was utilized to detect carbonates induced by bacterial carbonic anhydrase and elucidate their role in the solidification of sand particles. The findings indicate that the formation and development of biological soil crusts significantly enhance anti-scouribility. Comparison to those of bare coral sand, the shear stress increased from 0.35 to 1.11 N/m2 in the dark biocrusts. Moreover, significantly elevated carbonic anhydrase activity was observed in biological soil crusts, demonstrating a positive correlation with antiscouribility. In addition, there was a significant increase in bacterial abundance within the biological soil crusts. The enrichment of Cyanobacteriales and Chloroflexales potentially contributed to the increased carbonic anhydrase activity and antiscouribility. Furthermore, three cyanobacterial strains with carbonic anhydrase activity were isolated from biological soil crusts and subsequently confirmed to enhance sand solidification through microbial carbonate precipitation. This study presents initial evidence for the role of microbial carbonic anhydrase in enhancing the antiscouribility of biological soil crusts during their formation and development. These findings offer novel insights into the functional and mechanistic dimensions underlying the mitigation of soil erosion facilitated by biological soil crusts, which are valuable for implementing sustainable biorestoration and environmental management technologies to prevent soil erosion.

Decoupling the effects of air temperature change on soil erosion in Northeast China.

Changes in the air temperature tend to indirectly affect soil erosion by influencing rainfall, vegetation growth, economic development, and agricultural activities. In this study, the partial least squares-structural equation model (PLS-SEM) was used to decouple the impacts of temperature change on soil erosion in Northeast China from 2001 to 2019, and the indirect effect of temperature change on the pathways of natural and socioeconomic factors was analyzed. The results showed that temperature increase in Northeast China caused an increase in soil erosion by increasing rainfall and promoting economic development. Under the pathway of natural factors, in spring, the promoting effect on soil erosion under the influence of temperature change on rainfall was greater than the inhibiting effect on soil erosion under by the influence of temperature change on vegetation. In summer, the opposite effect was observed. Under the pathway of natural factors, over time, the promoting effect of temperature increase on soil erosion increased by 22.7%. Under the pathway of socioeconomic factors, temperature change not only aggravated soil erosion by promoting economic development, but also indirectly increased investments in agriculture and water conservation by improving the economy, thus inhibiting soil erosion to a certain extent. Over time, the contribution of temperature change to soil erosion through socioeconomic pathway was reduced by 44.4%. When the pathway of natural factors is compared with that of socioeconomics factors, temperature change imposed a more notable effect on the change in soil erosion through the socioeconomic pathway, indicating that human activities are the driving factors with a greater effect on soil erosion. Based on this, reasonable human intervention is an important means to alleviate soil erosion aggravation caused by rising temperatures.

Soil erosion, sediment sources, connectivity and suspended sediment yields in UK temperate agricultural catchments: Discrepancies and reconciliation of field-based measurements.

Robust understanding of the fine-grained sediment cascades of temperate agricultural catchments is essential for supporting targeted management for addressing the widely reported sediment problem. Within the UK, many independent field-based measurements of soil erosion, sediment sources and catchment suspended sediment yields have been published. However, attempts to review and assess the compatibility of these measurements are limited. The data available suggest that landscape scale net soil erosion rates (∼38 t km-2 yr-1 for arable and ∼26 t km-2 yr-1 grassland) are comparable to the typical suspended sediment yield of a UK catchment (∼44 t km2 yr-1). This finding cannot, however, be reconciled easily with current prevailing knowledge that agricultural topsoils dominate sediment contributions to watercourses, and that catchment sediment delivery ratios are typically low. Channel bank erosion rates can be high at landscape scale (27 km-2 yr-1) and account for these discrepancies but would need to be the dominant sediment source in most catchments, which does not agree with a review of sediment sources for the UK made in the recent past. A simple and robust colour-based sediment source tracing method using hydrogen peroxide sample treatment is therefore used in fifteen catchments to investigate their key sediment sources. Only in two of the catchments are eroding arable fields likely to be important sediment sources, supporting the alternative hypothesis that bank erosion is likely to be the dominant source of sediment in many UK catchments. It is concluded that the existing lines of evidence on the individual components of the fine sediment cascade in temperate agricultural catchments in the UK are difficult to reconcile and run the risk of best management interventions being targeted inappropriately. Recommendations for future research to address paucities in measured erosion rates, sediment delivery ratios and suspended sediment yields, validate sediment source fingerprinting results, consider the sources of sediment-associated organic matter, and re-visit soil erosion and sediment cascade model parameterisation are therefore made.

Spatial assessment of soil erosion by water using RUSLE model, remote sensing and GIS: a case study of Mellegue Watershed, Algeria-Tunisia.

Soil erosion is an important global phenomenon that can cause many impacts, like morphometry and hydrology alteration, land degradation and landslides. Moreover, soil loss has a significant effect on agricultural production by removing the most valuable and productive top soil's profile, leading to a reduction in yields, which requires a high production budget. The detrimental impact of soil erosion has reached alarming levels due to the exacerbation of global warming and drought, particularly in the arid climates prevalent in Tunisia and Algeria and other regions of North Africa. The influence of these environmental factors has been especially evident in the catchment of Mellegue, where profound vegetation loss and drastic changes in land use and cover, including the expansion of urban areas and altered agricultural practices, have played a significant role in accelerating water-induced soil loss between 2002 and 2018. The ramifications of these developments on the fragile ecosystems of the region cannot be overlooked. Accordingly, this study aimed to compare soil losses between 2002 and 2018 in the catchment of Mellegue, which is a large cross-border basin commonly shared by Tunisian-Algerian countries. The assessment and mapping of soil erosion risk were carried out by employing the Revised Universal Soil Loss Equation (RUSLE). This widely recognised equation provided valuable insights into the potential for erosion. Additionally, changes in land use and land cover during the same period were thoroughly analysed to identify any factors that may have contributed to the observed risk. By integrating these various elements, a comprehensive understanding of soil erosion dynamics was achieved, facilitating informed decision-making for effective land management and conservation efforts. It requires diverse factors that are integrated into the erosion process, such as topography, soil erodibility, rainfall erosivity, anti-erosion cultivation practice and vegetation cover. The computation of the various equation factors was applied in a GIS environment, using ArcGIS desktop 10.4. The results show that the catchment has undergone significant soil water erosion where it exhibits the appearance of approximately 14,000 new areas vulnerable to erosion by water in 2018 compared to 2002. Average erosion risk has also increased from 1.58 t/ha/year in 2002 to 1.78 in 2018, leading to an increase in total estimated soil loss of 54,000 t/ha in 2018 compared to around 25,500 t/ha in 2002. Maps of erosion risk show that highly eroded areas are more frequent downstream of the basin. These maps can be helpful for decision-makers to make better sustainable management plans and for land use preservation.

Spatial soil loss prediction impacted by long-term land use/land cover change: a case study of Swat District.

Soil erosion is a destructive consequence of land degradation caused by deforestation, improper farming practices, overgrazing, and urbanization. This irreversible effect negatively impacts the limited renewable soil resource, causing soil truncation, reduced fertility, and unstable slopes. To address the anticipation of erosion modulus resulting from long-term land use and land cover (LULC) changes, a study was conducted in the Swat District of Khyber Pakhtunkhwa (Kpk), Pakistan. The study aimed to predict and evaluate soil erosion concerning these changes using remote sensing (RS), geographic information systems (GIS), and the Revised Universal Soil Loss Equation (RUSLE) model. We also evaluated the impact of the Billion Tree Tsunami Project (BTTP) on soil erosion in the region. Model inputs, such as rainfall erosivity factor, topography factor, land cover and management factor, and erodibility factor, were used to calculate soil erosion. The results revealed that significant soil loss occurred under 2001, 2011, and 2021 LULC conditions, accounting for 67.26%, 61.78%, and 65.32%, falling within the category of low erosion potential. The vulnerable topographical features of the area indicated higher erosion modulus. The maximum soil loss rates observed in 2001, 2011, and 2021 were 80 t/ha-1/year-1, 120 t/ha-1/year-1, and 96 t/ha-1/year-1, respectively. However, the observed reduction in soil loss in 2021 as compared to 2001 and 2011 suggests a positive influence of the BTTP on soil conservation efforts. This study underscores the potential of afforestation initiatives like the BTTP in mitigating soil erosion and highlights the significance of environmental conservation programs in regions with vulnerable topography.

Prediction of soil erosion and sediment yield in an ungauged basin based on land use land cover changes.

Soil erosion is a significant problem in the agriculture sector and the environment globally. Susceptible soil erosion zones must be identified and erosion rates evaluated to decrease land degradation problems and increase crop productivity by protecting soil fertility. Therefore, a research study has been carried out in the Ponnaniyar River basin, an ungauged tributary of the Cauvery basin in India, primarily used for agriculture. The main purpose of this study is to assess soil erosion (SE) and sediment yield (SY) for the future in an ungauged basin by utilizing the projected land use/land cover (LULC) map of the study area. Additionally, Landsat 8 satellite dataset was only used for the classification and prediction of LULC to eliminate the variation between the resolution, bands and its wavelength of different satellites datasets. To achieve the goals of this study, three phases were followed. First, the LULC of the study area was classified using a Random Trees Classifier (RTC), a machine learning technique, followed by the projection of land cover using a Cellular Automata-based Artificial Neural Network (CA-ANN) model. The driving factors for this model include digital elevation model (DEM), slope, distance to roads, settlements, and water bodies. The accuracy level of the projected LULC map was determined by comparing it with the classified LULC map of the study area, and the results showed an overall accuracy (OA) of 85.35 percentage and a kappa coefficient (K) of 0.74, respectively. Second, the projected LULC map was used in the land management factor (C) and conversation practice factor (P) of the Revised Universal Soil Loss Equation (RUSLE) model to assess soil erosion. The model was integrated with the sediment delivery ratio (SDR) to estimate sediment yield within the study area. The accuracy of the generated erosion map based on the classified and projected LULC for the year 2022 was determined using the receiver operating characteristic curve (ROC) curve, and it was found to be in satisfactory agreement. Finally, for effective soil and water conservation measures, the basin was divided into 13 sub-watersheds (SWs) using terrain analysis in geographical information system (GIS). The SWs were prioritized based on the mean soil loss in the 4-year interval from 2014 to 2030 and integrated using the weighted average method to determine the final prioritization. From these findings, SW 11, SW 9, SW 12, and SW 1 are extremely affected by soil erosion, and immediate implementation of water harvesting structures is required for soil conservation. Also, this research might be useful for decision-makers and policymakers in land management.

Morphometric parameters based prioritization of watersheds for soil erosion risk in Upper Jhelum Sub-catchment, India.

Soil erosion is the inherent and destructive threat affecting agricultural production and livelihood of million mouths. The increased frequency of floods and land use/land cover changes has made Upper Jhelum Sub-catchment susceptible to soil erosion risk. Morphometric based watershed prioritization for soil erosion risk may help in sustainable management of natural resources. Thus, this paper endeavors to prioritize watersheds of Upper Jhelum Sub-catchment in India based on morphometric parameters for soil erosion risk using geospatial techniques. Weights to the morphometric parameters were assigned through a multi-criteria decision method. The watersheds in the Sub-catchment have been categorized into low, medium, high and very high priority classes based on prioritization ranks that were determined by computing the compound value for the soil erosion risk, based on prioritization ranks obtained through compound value for the soil erosion risk. The results revealed 1E1D3 and 1E1D8 watersheds accorded very high priority. The watersheds namely IE1D2 and IEID4 were found under high priority. Medium priority for soil erosion risk was determined in IEID5 and IED7 watersheds while 1E1D1 and IE1D6 watersheds were identified for low priority. The study calls for implementing soil conservation practices in the Sub-catchment. The Sub-catchment can be made less hazardous for the soil erosion risk by implementing contour farming, building check dams, terrace farming, afforestation and limiting large scale overgrazing. The findings of this study may offer valuable insights for stakeholders for conservation of soil resource. The approach utilized in the study may be linked with soil loss estimation for effective conservation of natural resources in further future studies.

Soil erosion vulnerability and soil loss estimation for Siran River watershed, Pakistan: an integrated GIS and remote sensing approach.

Soil erosion is a problematic issue with detrimental effects on agriculture and water resources, particularly in countries like Pakistan that heavily rely on farming. The condition of major reservoirs, such as Tarbela, Mangla, and Warsak, is crucial for ensuring an adequate water supply for agriculture in Pakistan. The Kunhar and Siran rivers flow practically parallel, and the environment surrounding both rivers' basins is nearly identical. The Kunhar River is one of KP's dirtiest rivers that carries 0.1 million tons of suspended sediment to the Mangla reservoir. In contrast, the Siran River basin is largely unexplored. Therefore, this study focuses on the Siran River basin in the district of Manshera, Pakistan, aiming to assess annual soil loss and identify erosion-prone regions. Siran River average annual total soil loss million tons/year is 0.154. To achieve this, the researchers integrate Geographical Information System (GIS) and remote sensing (RS) data with the Revised Universal Soil Loss Equation (RUSLE) model. Five key variables, rainfall, land use land cover (LULC), slope, soil types, and crop management, were examined to estimate the soil loss. The findings indicate diverse soil loss causes, and the basin's northern parts experience significant soil erosion. The study estimated that annual soil loss from the Siran River basin is 0.154 million tons with an average rate of 0.871 tons per hectare per year. RUSLE model combined with GIS/RS is an efficient technique for calculating soil loss and identifying erosion-prone areas. Stakeholders such as policymakers, farmers, and conservationists can utilize this information to target efforts and reduce soil loss in specific areas. Overall, the study's results have the potential to advance initiatives aimed at safeguarding the Siran River watershed and its vital resources. Protecting soil resources and ensuring adequate water supplies are crucial for sustainable agriculture and economic development in Pakistan.

Soil erosion estimation and erosion risk area prioritization using GIS-based RUSLE model and identification of conservation strategies in Jejebe watershed, Southwestern Ethiopia.

Erosion of soil refers to the process of detaching and transporting topsoil from the land surface by natural forces such as water, wind, and other factors. As a result of this process, soil fertility is lost, water bodies' depth is reduced, water turbidity rises, and flood hazard problems, etc. Using a numerical model of erosion rates and erosion risks in the Jejebe watershed of the Baro Akobo basin in western Ethiopia, this study mapped erosion risks to prioritize conservation measures. In this study, the Revised Universal Soil Loss Equation (RUSLE) model was used, which was adapted to Ethiopian conditions. To estimate soil loss with RUSLE, the rainfall erosivity (R) factor was generated by interpolating rainfall data, the soil erodibility (K) factor was derived from the soil map, the topography (LS) factor was determined from the digital elevation model (DEM), cover and management (C) factor derived from the land use/cover data, and conservation practices (P) factor generated from digital elevation model (DEM) and land use/cover data were integrated with remote sensing data and the GIS 10.5 environment. The findings indicated that the watershed annual soil loss varies from nearly 0 on a gentle slope of forest lands to 265.8 t ha-1 year-1 in the very steep slope upper part of the watershed, with a mean annual soil loss of 36.2 t ha-1 year-1. The total annual soil loss in the watershed is estimated to be around 919,886.5 tons per year. To minimize the amount of soil erosion in the watershed that had been most severely affected, we identified eight conservation strategies that could be implemented. These strategies were based on the participatory watershed development (PWD) principles established by the Ethiopian government and the severity of the erosion in the watershed. The study's findings showed that a GIS-based RUSLE soil erosion assessment model can provide a realistic prediction of the amount of soil loss that will occur in the watershed. This tool can also help identify the priority areas for implementing effective erosion control measures.