Soil Erosion Rates Research Articles

Infiltration-Based Variability of Soil Erodibility Parameters Evaluated with the Jet Erosion Test

Soil erosion by water on agricultural hillslopes leads to numerous environmental problems including reservoir sedimentation, loss of agricultural land, declines in drinking water quality, and requires deep understanding of underlying physical processes for better mitigation. It is imperative to accurately predict soil erosion caused by overland flow processes so that soil conservation efforts can be undertaken proactively before large-scale sedimentation problems arise. Soil detachment is often described by the excess shear stress equation that contains two physical soil erodibility parameters, erodibility coefficient, and critical shear stress. These parameters are normally assumed to be constant but can change across varying soil texture classes as well as during surface runoff events due to changes in soil cohesion and potential dependency on soil moisture content. These changes may significantly affect soil erosion rates at the field and watershed scale. In this study, the erodibility parameters of three soil types (sandy loam, clay loam, and silty clay loam) were analyzed using a laboratory mini-Jet Erosion Test (JET) to determine the effect of soil sample infiltration and moisture condition. Results from the experiments depicted a dynamic relationship between the soil erodibility parameters and amount of infiltrated mass of water. Data analysis displayed that for soils of different texture critical shear stress exhibited local minimum with higher values for very dry and saturated soils, while erodibility coefficient tended to increase with the increase of mass of soil water. Utilizing these dynamic soil erodibility parameters did not result in a significant difference in soil erosion rates when compared to using the averaged soil erodibility parameters taken from the experiment but the range of potential erosion rates increases with the increase of applied sheer stress to soil surface. The erosion rates with the experiment-based coefficients were found to be higher than with the baseline WEPP-based coefficients. These results highlight the importance of evaluating the effect of intrastorm dependent factors during surface runoff events, such as antecedent soil moisture content, time to peak from the start of runoff, soil cohesion, etc., on soil erodibility parameters to accurately calculate erosion rates, especially for initially dry soils or during earlier stages of surface runoff when critical shear stresses were highly affected. Further assessment of such factors with JET or other laboratory and field tests is recommended.

SPATIAL ESTIMATION OF SOIL EROSION USING GEOSPATIAL TECHNIQUE – A CASE STUDY OF JANJEVA RIVER CATCHMENT (KOSOVO)

The aim of the study is to analyse the spatial estimation of soil erosion in a small size river catchment of Janjeva (Kosovo). Soil erosion is becoming a serious threat and its spatial estimation is crucial for soil resource protection and management. The Revised Universal Soil Loss Equation (RUSLE) methodology integrated with GIS techniques was applied to estimate the annual erosion rate. Different datasets including open-source data were used to find main components of soil erosion. The results show different soil erosion classes depending on lithological settings, landforms, climate conditions, soil properties, land cover and soil conservation practices. By calculating RUSLE parameters for Janjeva River catchment (84 km²), we found out that mean annual erosion rate is 1 t·ha-¹·yr-¹. Erosion rate class <5 t·ha-¹·yr-¹ dominates the catchment’s area with 92.5%, while other classes have 7.5% of catchments total area. Highest rates of soil erosion are found in volcanic rocks, steep slopes and soils without conservation practices. Soils located in western part of the catchment with adequate conservation practice have minimum erosion rate.

Agricultural land abandonment and its impact on soil erosion in the Madi Watershed, Gandaki Province, Nepal

Agricultural land abandonment is the crucial issue of land use /land cover change in many parts of the world and it is directly related to soil erosion in the mountain areas. Nepal has also faced heavy agricultural land abandonment from the mountain regions in the last two decades. This study is concerned with agricultural land abandonment and its impact on soil erosion in the Madi Watershed, Gandaki Province of Nepal. This study used high-resolution aerial photography and Google Earth images to map cultivated land and its abandonment in 1995 and 2020. The Revised Universal Soil Loss Equation (RUSLE) model has been used to estimate soil erosion. Studies revealed that more than 40% of the agricultural land was abandoned from 1995 to 2020 and there is higher spatial variability of abandonment intensity. High altitude and steeper slope areas have a higher intensity of abandonment than in lower altitude and lower slope gradients. There is a significant impact of abandonment of agricultural land on reducing soil erosion from 1995 to 2020. The average rate of soil erosion was quite high in 1995 but decreased to 51.5 percent in 2020. There are higher rates of reduction in soil erosion at higher altitudes and marginal lands like steeper slopes and the areas having lower solar radiation because of the higher proportion of agricultural land abandonment. Thus, it can be concluded that agricultural land abandonment during the last 25 years significantly impacts soil erosion control in the study area.

Effects of hillslope aspect on erosion rate of alpine meadows in the Three-River Headwater Region, China

Soil erosion causes serious grassland degradation in the Three-River Headwater Region (TRHR) of the Qinghai-Tibet Plateau. Identifying source areas of erosion is important, including understanding the influences of hillslope aspect on soil erosion. However, the effect of hillslope aspect on soil erosion is a much-debated process, wherein contrasting results were previously reported. We hypothesized that aspect-induced differences in environmental variables will be related to differences in erosion magnitude and spatial pattern, and that these differences will impact soil physiochemical characteristics as well. To test this hypothesis, soil samples were collected at conjoined south- and north-facing hillslopes along elevational profiles in a small watershed in Yushu County, with measurements of soil water content (SWC), soil organic carbon (SOC), soil organic matter (SOM), soil particle size distribution, soil total nitrogen (STN) and phosphorus (STP). Soil erosion rate was estimated using 137Cs technology. The results showed that soil erosion rates of the two hillslopes ranged from 0.073 to 10.83 t ha-1 yr-1, and were 3 times greater on the south-facing hillslope. Soil water content ranged from 7.6% to 76.8% on the two hillslopes with lower values on the south-facing hillslope due to the greater solar radiation. By Spearman correlation analysis and path analysis, we concluded that lower soil water content on the south-facing hillslope restricts vegetation growth, and hence resulting in greater soil erosion under the case where vegetation growth is dominantly controlled by water availability. Greater soil erosion on the south-facing hillslope caused greater surficial accumulation of coarser materials and greater loss of soil nutrients, which are expected to complicate the hydrological erosion process. Moreover, the downslope increased soil erosion rate should be fully considered in conservation practices. These results will improve our understanding of the interaction and feedback mechanisms between soil characteristics, vegetation function, and soil erosion in the TRHR.

Performance And Adoptability Of Mulching Technology To Control Soil Erosion: Case Study Of The Sebeya Catchment In Rwanda

Soil erosion is a pressing environmental concern that poses significant threats to agricultural productivity, watershed health, and ecosystem stability. This research investigates the performance and adoptability of mulching technology as a Soil Erosion Control Measure (SECM) within the Sebeya catchment. This study employed various methods including a review of existing literature, on-site visits, structured interviews, and focus group discussions to evaluate the factors contributing to soil erosion, its impacts, and the variety of SECM within the Sebeya catchment. Among the 96 farmers surveyed in this research, it was evident that the natural reasons for soil erosion in the Sebeya drainage area were often attributed to the intense rainfall (23%) and steep slopes (22%). Also, the influence of lack of SECM and the continuous ploughing is significant with 22% and 22% respectively. The availability of mulching materials can vary significantly based on the geographic location, agricultural practices, and economic factors. In the Sebeya catchment, mulching materials often sourced from crop residues and vegetative residues. To address the risks associated with soil erosion, various site-specific measures were recommended. Using the Universal Soil Erosion Equation (USLE) model, the suggested Soil Erosion Control measures (SECM) were simulated with a significant decrease in soil loss, dropping from 73.05 t/ha/y to 19.62 t/ha/y. By incorporating mulching technology into the recommended SECM to mitigate soil erosion, the soil erosion rates reduced to permissible soil loss from 19.62 t/ha/y to 11.26 t/ha/y. To effectively reduce the high rates of soil erosion to acceptable levels within the Sebeya drainage area, this study advocates for the implementation of the recommended site-specific soil erosion control measures combined with mulching, drainage channels, and the stabilizing grasses on the same farmland. Implementing SECM stands as the optimal choice for enhancing soil productivity while reducing sedimentation in downstream rivers and lakes.
 

Sediment sorting and transport mechanism controlled by both soil properties and hydraulic parameters on hillslopes

Understanding the sediment sorting and transport processes is is crucial for enhancing the understanding of soil erosion mechanisms and improving soil erosion prediction. However, quantitative studies based on the coupling effects of both hydraulic parameters and soil properties are still lacking. In this study, five loessial soils with varying physicochemical properties were collected in the Loess Plateau of China, and simulated rainfall experiments were carried out in a metal box with a slope of 20 degrees under rainfall intensities of 1, 1.5, and 2 mm min−1. Runoff samples were collected to analyze the variation in erosion rates and effective particle size distribution of eroded sediments during the rainfall process. The results showed that the stream power was the optimal parameter to model the erosion rate, and a power function incorporating the clay content and stream power could well predict the erosion rate of different soils. The enrichment ratio indicated the enrichment of fine particles and depletion of coarse particles. And the sediment sorting degree increased with increasing soil clay content. The critical particle size for distinguishing different transport mechanisms varied among soils, with more than 55.46 % of the total sediment transported by suspension/saltation. A linear function and power function including the original soil particle size distribution and stream power were developed to quantify the sediment clay content and the relative contribution of different transport mechanisms. This study could be helpful to improve the soil erosion prediction model and provide basic guidelines for regional soil and water conservation.

Spatial Quantification of Cropland Soil Erosion Dynamics in the Yunnan Plateau Based on Sampling Survey and Multi-Source LUCC Data

The mapping and dynamic monitoring of large-scale cropland erosion rates are critical for agricultural planning but extremely challenging. In this study, using field investigation data collected from 20,155 land parcels in 2817 sample units in the National Soil Erosion Survey, as well as land use change data for two decades from the National Land Use/Cover Database of China (NLUD-C), we proposed a new point-to-surface approach to quantitatively assess long-term cropland erosion based on the CSLE model and non-homologous data voting. The results show that cropland in Yunnan suffers from serious problems, with an unsustainable mean soil erosion rate of 40.47 t/(ha·a) and an erosion ratio of 70.11%, which are significantly higher than those of other land types. Engineering control measures (ECMS) have a profound impact on reducing soil erosion; the soil erosion rates of cropland with and without ECMs differ more than five-fold. Over the past two decades, the cropland area in Yunnan has continued to decrease, with a net reduction of 7461.83 km2 and a ratio of −10.55%, causing a corresponding 0.32 × 108 t (12.12%) reduction in cropland soil loss. We also quantified the impact of different LUCC scenarios on cropland erosion, and extraordinarily high variability was found in soil loss in different basins and periods. Conversion from cropland to forest contributes the most to cropland erosion reduction, while conversion from grassland to cropland contributes 56.18% of the increase in soil erosion. Considering the current speed of cropland regulation, it is the sharp reduction in land area that leads to cropland erosion reduction rather than treatments. The choice between the Grain for Green Policy and Cropland Protecting Strategy in mountainous areas should be made carefully, with understanding and collaboration between different roles.

Quantifying Soil Erosion in Drought-Impacted Central Odisha, India, through Geospatial Mapping with RUSLE

Soil degradation in Odisha poses a significant conservation concern for the local environment. The present research focused on a region in central Odisha State, India, affected by drought conditions. Several models have emerged to assess soil loss, with the Revised Universal Soil Loss Equation (RUSLE) standing out as the most suitable option. The erosion computation process entails utilizing the digital elevation model (DEM), Landsat-9 imagery, and soil data from several sources accessible in different forms and scales. The present analysis took into account various elements, namely, crop management factor (C), practice management factor (P), slope length factor (LS), steepness factor of the slope (S), and rainfall factor (R). Multiplying these factors yielded the average rate of soil erosion. Areas with a high slope length factor, such as those in Kandhamal, Kalahandi, and Nuapada, have a high erosion rate. The study reveals that 57% of the land in the study area experiences very low to moderate soil erosion at a rate of 2–10 tons per hectare per year, while 43% faces moderately to very severe erosion at a rate of 10–25 tons per hectare per year. Erosion hotspots, covering 32,205 square kilometers, are mainly identified in agricultural and forested hilly areas where slopes exceed 10°, such as those in Kandhamal, Kalahandi, and Nuapada, which have a high erosion rate. These districts are especially vulnerable to soil loss and resulting climate action (Sustainable Development Goals-13) because of frequent and severe rainfall, shifting agricultural practices, a thin surface soil covering, natural erosion, and barren hills. The research emphasizes the urgent need for implementing conservation and management measures to protect high-risk areas from further degradation. In conclusion, the study underscores the effectiveness of the RUSLE-GIS model in conducting quantitative and spatial assessments of soil erosion on a river watershed scale. The model is deemed crucial in formulating conservation strategies to address the identified erosion issues in the tropical highlands of the area.

Soil erosion-based sub-watershed prioritization through coupling various crop management and erosivity scenarios using game theory

The soil erosion of the watershed is different in temporal and spatial scales due to complex climatic and environmental conditions and their dynamic state over time. Accordingly, it is necessary to prioritize sub-watersheds based on their dynamic conditions to reduce the destructive effects of soil erosion. However, this issue has to be sufficiently reported on the scale of the watershed. Towards that, a game theory-based prioritization approach was planned concerning changes in vegetation cover and rainfall in the Shazand Watershed of the Markazi Province, Iran. To achieve the purpose of the study, the amount of soil erosion was first estimated in different scenarios resulting from the changes in rainfall erosivity and vegetation cover using the RUSLE model. Next, pairwise comparisons between 24 sub-watersheds in all scenarios were made based on the sub-watersheds' ranks in soil erosion in each scenario. Considering all scenarios, the priority of the sub-watersheds was assessed using the Condorcet approach. The results showed that the mean soil erosion in the watershed ranged from 5.4 and 36 t ha−1 y−1 while applying various scenarios. It is worth mentioning that the prioritization results obtained from the Condorcet algorithm and the current soil erosion rate are highly similar. On the other hand, sub-watersheds 2 and 9 were selected as the first and last priority, providing an appropriate roadmap for managers and relevant departments to adopt appropriate soil erosion inhibition measures.

Assessment of soil erosion in the Irga watershed on the eastern edge of the Chota Nagpur Plateau, India

Human activities to improve the quality of life have accelerated the natural rate of soil erosion. In turn, these natural disasters have taken a great impact on humans. Human activities, particularly the conversion of vegetated land into agricultural land and built-up area, stand out as primary contributors to soil erosion. The present study investigated the risk of soil erosion in the Irga watershed located on the eastern fringe of the Chota Nagpur Plateau in Jharkhand, India, which is dominated by sandy loam and sandy clay loam soil with low soil organic carbon (SOC) content. The study used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) technique to determine the rate of soil erosion. The five parameters (rainfall-runoff erosivity (R) factor, soil erodibility (K) factor, slope length and steepness (LS) factor, cover-management (C) factor, and support practice (P) factor) of the RUSLE were applied to present a more accurate distribution characteristic of soil erosion in the Irga watershed. The result shows that the R factor is positively correlated with rainfall and follows the same distribution pattern as the rainfall. The K factor values in the northern part of the study area are relatively low, while they are relatively high in the southern part. The mean value of the LS factor is 2.74, which is low due to the flat terrain of the Irga watershed. There is a negative linear correlation between Normalized Difference Vegetation Index (NDVI) and the C factor, and the high values of the C factor are observed in places with low NDVI. The mean value of the P factor is 0.210, with a range from 0.000 to 1.000. After calculating all parameters, we obtained the average soil erosion rate of 1.43 t/(hm2•a), with the highest rate reaching as high as 32.71 t/(hm2•a). Therefore, the study area faces a low risk of soil erosion. However, preventative measures are essential to avoid future damage to productive and constructive activities caused by soil erosion. This study also identifies the spatial distribution of soil erosion rate, which will help policy-makers to implement targeted soil erosion control measures.

Mapping and Quantifying Integrated Land Degradation Status of Goa Using Geostatistical Approach and Remote Sensing Data

Globally, land degradation is becoming a grave concern. Over the years, conditions such as drought, extreme weather events, pollution, changes in land use land cover, and desertification have intensified and led to land degradation, affecting both ecological and economic processes. Equally, during the last two centuries, population and urbanization have amplified manifold and increased the demand for additional food and shelter, resulting in alteration in land use land cover, over-grazing, and over-cultivation, loss of nutrient-rich surface soil, greater runoff from the more impermeable subsoil, and reduced water availability. Geographically, Goa is a highly diversified state. It is sandwiched between the West Coast and the Western Ghats. The state is blessed with beaches, mangroves, backwaters, wetlands, wildlife sanctuaries, evergreen forests, barren lands, and other vital ecosystems. The State of Goa, on average, receives more than 3000 millimeters of rainfall annually with high surface runoff. Using both primary and secondary data, this study sought to investigate and quantify the state’s land degradation. Secondary data came from satellites and other sources, while primary data came from field observation and ground truthing. Land degradation factors related to soil loss and the spatial pattern of soil erosion are predicted and evaluated using the Revised Universal Soil Loss Equation (RUSLE) method. Landsat-8 OLI-TIRS images were utilized to decide land use and cover (C factor), while DEM information was utilized to assess (LS factor). A soil map and rainfall data were collected to acquire a better understanding of soil erodibility (K factor) and rainfall erosivity (R factor). The kriging interpolation technique was used to gain a deeper comprehension of land degradation.The purpose of this paper is to comprehend the concept of integrated land degradation and how it affects the environment of Goa. Using remote sensing data and geostatistical methods, the study creates a comprehensive map of land degradation in the region by identifying and analyzing the various forms of land degradation in Goa. The paper also looks at how rainfall and the amount of land cover affect the rate of soil erosion in Goa. According to the findings, intense rainfall makes the eastern part of Goa particularly susceptible to soil erosion, and bare soil has a greater potential for erosion than vegetated land. The paper concludes that comprehensive land degradation mapping can be a useful tool for developing efficient land management strategies to preserve soil and encourage sustainable development in the region.

Assessing the Influence of Multiresolution DEMs on Soil Loss Prediction using the RUSLE Model in Central Morocco

Abstract The topography plays a significant role in determining the rate of soil loss. The Digital Elevation Model (DEM) retrieved from earth observation products can be used to calculate the slope length and steepness, which are important factors in the Revised Universal Soil Loss Equation (RUSLE) used to estimate soil erosion. In the present study, the effect of two DEM resolutions (30m and 90 m) on RUSLE model results was assessed and used to quantify the rate of soil loss in Settat province (Morocco), specifically in certain abandoned quarries. As a result, DEM-30 and DEM-90 soil erosion rates vary from 0 to 282.77 t.ha-1.yr-1 and 0 to 13.79 t.ha-1.yr-1, respectively. At the quarry level, the abandoned quarries showed soil loss rates ranging from 0 to 7.92 t.ha-1.yr-1 for DEM-30. Contrary to this, the soil loss rate for DEM-90 data was zero. To summarize, for more relevant and detailed conclusions, high-resolution data must be used to collect more information and describe the erosion process with as much detail as possible, especially for small areas.

THE EFFECT OF STEEP SLOPES ON THE APPLICATION OF THE USLE, RUSLE, AND MUSLE METHODS

Soil erosion and ecological environmental damage cause environmental and resource problems in the Way Khilau Sub-Sub-Watershed. The purpose of the study was to compare the predictions of the soil erosion rates of the universal soil loss equation (USLE), its revised model (RUSLE), and its modified version (MUSLE). This study comprises several stages; literature review, data collection, and erosion calculations. The erosion calculations were based on 3 methods; THE USLE, RUSLE and MUSLE methods, which were then analyzed for the results of the comparison. The largest erosion values of all the methods on steep slope land (25-45%) were 526.5485 tons/Ha/th with the USLE Method, 585.3 tons/Ha/th with the RUSLE Method, and 13202.38 tons/Ha/th with the MUSLE Method. The lowest erosion values of all methods on sloping slope land (0-8%) were 0.879 tons/Ha/th with the USLE Method, 0.94 tons/Ha/th with the RUSLE Method, and 22.04 tons/Ha/th with the MUSLE Method. The results of the calculations of the average erosion per year in the Way Khilau Sub-Sub-Watershed with the USLE and RUSLE methods fall into the medium category (S), while with the MUSLE Method, it falls into the very heavy category (SB). In conclusion, the USLE and RUSLE soil erosion models had relatively similar results, yet the MUSLE model showed a higher spatial difference in erosion potential than the other models.

Prioritization of sub-watersheds and subsequent site identification for soil water and conservation practices using the SWAT-AHP integrated model in the Lower Sutlej Sub-basin, India.

Prioritization of watersheds is a crucial step in integrated river basin management. It guides resource allocation, planning, decision-making, stakeholder engagement, targeted interventions, and monitoring and evaluation efforts. By identifying and addressing priority watersheds, comprehensive and sustainable management of water resources can be achieved within a river basin. The aim of the current study is to prioritize watersheds using the Soil and Water Assessment Tool (SWAT) and site suitability analysis for the implementation of soil and water conservation structures (SWCS) in the prioritized watersheds by using an analytical hierarchy process (AHP) of the Lower Sutlej Sub-basin, India. The model was calibrated with observed data from 2017 to 2019 with the first 2years (2015-16) as a warm-up period. Furthermore, validation of the model was done using 2-year data from 2020 to 2021. The model showed successful performance in terms of the R2 range from 0.72 to 0.89, the NSE range from 0.67 to 0.73, the PBIAS range from - 26.70 to 11.30, and the RSR range from 0.51 to 0.57 for stream flow and sediment yield during calibration and validation period. The basin's average annual soil loss ranged from 3.08 to 21.63 t/ha/year, a watershed with the WS2 index seeing the highest rate of soil erosion (21.63 t/ha/year). Hence, WS2 was found to be a top priority. In addition, the site suitability analysis of the prioritized watershed (WS2) reveals that about 1.42% of the area is extremely suitable, 16.14% is highly suitable, and 35.58% is moderately suitable for SWCS. According to the site suitability map validation, both dam locations were found in highly suitable areas, so the developed site suitability map is accurate. This research will help sustainability planners and managers make more informed decisions when building SWCS at suitable sites for better land and water conservation.

Monitoring and Quantifying Soil Erosion and Sedimentation Rates in Centimeter Accuracy Using UAV-Photogrammetry, GNSS, and t-LiDAR in a Post-Fire Setting

Remote sensing techniques, namely Unmanned Aerial Vehicle (UAV) photogrammetry and t-LiDAR (terrestrial Light Detection and Ranging), two well-established techniques, were applied for seven years in a mountainous Mediterranean catchment in Greece (Ilioupoli test site, Athens), following a wildfire event in 2015. The goal was to monitor and quantify soil erosion and sedimentation rates with cm accuracy. As the frequency of wildfires in the Mediterranean has increased, this study aims to present a methodological approach for monitoring and quantifying soil erosion and sedimentation rates in post-fire conditions, through high spatial resolution field measurements acquired using a UAV survey and a t-LiDAR (or TLS—Terrestrial Laser Scanning), in combination with georadar profiles (Ground Penetration Radar—GPR) and GNSS. This test site revealed that 40 m3 of sediment was deposited following the first intense autumn rainfall events, a value that was decreased by 50% over the next six months (20 m3). The UAV–SfM technique revealed only 2 m3 of sediment deposition during the 2018–2019 analysis, highlighting the decrease in soil erosion rates three years after the wildfire event. In the following years (2017–2021), erosion and sedimentation decreased further, confirming the theoretical pattern, whereas sedimentation over the first year after the fire was very high and then sharply lessened as vegetation regenerated. The methodology proposed in this research can serve as a valuable guide for achieving high-precision sediment yield deposition measurements based on a detailed analysis of 3D modeling and a point cloud comparison, specifically leveraging the dense data collection facilitated by UAV–SfM and TLS technology. The resulting point clouds effectively replicate the fine details of the topsoil microtopography within the upland dam basin, as highlighted by the profile analysis. Overall, this research clearly demonstrates that after monitoring the upland area in post-fire conditions, the UAV–SfM method and LiDAR cm-scale data offer a realistic assessment of the retention dam’s life expectancy and management planning. These observations are especially crucial for assessing the impacts in the wildfire-affected areas, the implementation of mitigation strategies, and the construction and maintenance of retention dams.

Characterization of carbon fluxes, stock and nutrients in the sacred forest groves and invasive vegetation stands within the human dominated landscapes of a tropical semi-arid region

In the semi-arid plains of Southern India, outside the protected area network, sacred groves forests and the barren lands invaded by Prosopis juliflora are reckoned to be the major greenery, but have homogenous and heterogeneous vegetation respectively. This study attempted to compare 50 Sacred Groves Stands (SGS) and 50 monodominant Prosopis juliflora Stands (PJS) for the functional diversity, evenness, floral diversity, carbon stock and dynamics, carbon-fixing traits, dendrochronology of trees, soil nutrient profiles, and soil erosion. Quadrat sample survey was adopted to record stand density, species richness, abundance, basal area and leaf area index; composite soil samples were collected at depths 0–30 cm for nutrient profiling (N, P, K, and OC). Photosynthesis rate (µmole co2 m2/sec), air temperature (°c), leaf intracellular co2 concentration (ppm), ambient photosynthetic active radiation (µmole m2/sec), transpiration rate (m. mole H2O m2/sec) were determined for the 51 tree species existed in SGS and PJS using Plant Photosynthesis system. Structural Equation Model (SEM) was applied to derive the carbon sequestering potential and photosynthetic efficiency of eight dominant tree species using vital input parameters, including eco-physiological, morphological, and biochemical characterization. The Revised Universal Soil Loss Equation (RUSLE) model, in conjunction with ArcGIS Pro and ArcGIS 10.3, was adopted to map soil loss. Carbon source/sink determinations inferred through Net Ecosystem Productivity (NEP) assessments showed that mature SGS potentially acted as a carbon sink (0.06 ± 0.01 g C/m2/day), while matured PJS acted as a carbon source (−0.34 ± 0.12 g C/m2/day). Soil erosion rates were significantly greater (29.5 ± 13.4 ton/ha/year) in SGS compared to PJS (7.52 ± 2.55 ton/ha/year). Of the eight selected tree species, SEM revealed that trees belonging to the family Fabaceae [Wrightia tinctoria (estimated coefficient: 1.28, p = 0.02) > Prosopis juliflora (1.22, p = 0.01) > Acacia nilotica (1.21, p = 0.03) > Albizia lebbeck (0.97, p = 0.01)] showed comparatively high carbon sequestering ability.

Modeling the impact of land use land cover change on the estimation of soil loss and sediment export using InVEST model at the Rib watershed of Upper Blue Nile Basin, Ethiopia

Information on soil loss and sediment export is essential to identify vulnerable area of soil erosion and to inform conservation interventions in a given watershed. The goal of this study was to analyze the changes in soil loss and sediment exports in the Rib watershed of Ethiopia's Upper Blue Nile Basin. The study used spatial data by using a variety of data sources, including topographic maps, soil maps, meteorological data, and satellite images. Cultivated land, forests, grazing areas, shrubs, water bodies, and settlements were all identified in the study watershed. Soil loss and sediment export were calculated using the Integrated Valuation of Ecosystem Services and Tradeoff (In-VEST) model. The model was calibrated using the sediment yield data gathered in the sample watersheds. The results reveal that while the equivalent sediment export grew from 6.54 t/ha/year to 11.05 t/ha/year in 2000 and 2020, respectively, the average soil loss increased from 22.37 t/ha/year in 2000 to 33.38 t/ha/year in 2020. The largest rate of soil erosion was seen on cultivated land, which increased from 40.86 t/ha/year in 2000 to 53.9 t/ha/year in 2020. This relates to the expansion of the agricultural land. The soil loss and sediment export rates in sub-watersheds three (SW-3) and five (SW-5) were the highest, at 61.80 and 63.48 t/ha/year and 18.75 and 19.35 t/ha/year, respectively. The least amount of soil loss occurs in sub-watershed twelve (SW-12) (2.56 t/ha/year). This is because SW-12 is situated in the watershed's lower reaches fogera plain parts of the watershed experiencing less erosion. The result concluded that prioritizing those sub-watersheds is important for informed decision-making processes.

Effect of climate change on soil erosion rate in a tropical Indian catchment

Abstract This study analyzes the variations in soil erosion rate in a tropical catchment in India using the empirical Revised Universal Soil Loss Equation (RUSLE) model integrated with climate change scenarios from an ensemble of global climate models (GCMs) included in the NEX Global Daily Downscaled Projections Coupled Model Intercomparison Project Phase 6 dataset for Shared Socioeconomic Pathways (SSP) 126 and SSP 585. A set of seven GCMs are initially selected. Based on their ability to simulate the rainfall for the current scenario, the PROMETHEE-II method is used to rank the GCMs and the top four best-performing models are used for further analysis. Soil erosion rates projected for the future climate scenarios are compared with the current scenario. In the near future and in the middle of the century, soil erosion rates under the SSP 126 scenario are projected to be higher than that under the SSP 585 scenario. The ensemble average soil erosion rate is projected to increase by 15.41%–25.94% toward the end of the century for different emission scenarios, and the areas susceptible to high and very high soil erosion rates are projected to increase to 40.3%.

Estimation of Water Yield and Soil Erosion in Samanalawewa Watershed in Sri Lanka using GIS-based InVEST Model

Ecosystem services (ES) are a group of tasks performed by the earth's ecosystems that are required to support life and offer benefits to humanity. Thus, this study explores two of the water-related ecosystem services, water yield, and soil retention that were distributed in the Samanalawewa Watershed (SW) and its eight sub-watersheds in Sri Lanka, over 20 years (2000-2020) with five- year time intervals. Soil and water conservation and water yield play an important role in ecosystem management. Hydrological balance is a crucial component of the hydrological ecosystem services. Assessing water yield and soil erosion are pivotal for watershed management. Thus, this study estimated and mapped the water yield and soil erosion, using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST 3.9.2) Annual Water Yield (AWY) and Sediment Delivery Ratio (SDR) model respectively. According to the obtained results, in 2000, 2005, 2010, 2015 and 2020, the estimated mean annual water yield was 2.62x105, 2.6x105, 3.5x105, 3.58x105 and 2.75x105 m3 ha-1year-1, respectively. Furthermore, the estimated mean annual soil erosion rates for the above- mentioned years were 53.2, 52.9, 69.7, 87.7 and 70.2 t ha-1 year-1. The estimated soil loss values of the SW are 10 to 18 times greater than the soil erosion tolerance (5 t ha-1 year-1) in Sri Lanka. The results show that the years 2015 and 2005 have the highest and the lowest water yield and total soil loss values, respectively. The upper part of the watershed has relatively moderate water yield and soil loss values than the lower part. These findings would be beneficial in developing watershed management strategies and in the implementation of suitable soil and water conservation techniques within the watershed. 
 Keywords: Ecosystem services, InVEST, Samanalawewa watershed, Soil erosion, Water yield

Measuring soil erosion rates in Hyrcanian forests: An application of the 137Cs method

Measuring soil erosion rates in Hyrcanian forests: An application of the 137Cs method