Soil Erosion Potential Research Articles

Multi-hazard modeling of erosion and landslide susceptibility at the national scale in the example of North Macedonia

Abstract Due to favorable natural conditions and human impact, the territory of North Macedonia is very susceptible to natural hazards. Steep hillslopes combined with soft rocks (schists on the mountains; sands and sandstones in depressions), erodible soils, semiarid continental climate, and sparse vegetation cover give a high potential for soil erosion and landslides. For this reason, this study presents a multi-hazard approach to geohazard modeling on the national extent in the example of North Macedonia. Utilizing Geographic Information Systems, relevant data about the entire research area were employed to analyze and assess soil erosion and susceptibility to landslides and identify areas prone to both hazards. Using the Gavrilović Erosion Potential Method (EPM), an average value of 0.36 was obtained for the erosion coefficient Z, indicating low to moderate susceptibility to erosion. However, a significant area of the country (9.6%) is susceptible to high and excess erosion rates. For the landslide susceptibility assessment (LSA), the Analytical hierarchy process approach is combined with the statistical method (frequency ratio), showing that 29.3% of the territory belongs to the zone of high and very high landslide susceptibility. Then, the accuracy assessment is performed for both procedures (EPM and LSA), showing acceptable reliability. By overlapping both models, a multi-hazard map is prepared, indicating that 22.3% of North Macedonia territory is highly susceptible to erosion and landslides. The primary objective of multi-hazard modeling is to identify and delineate hazardous areas, thereby aiding in activities to reduce the hazards and mitigate future damage. This becomes particularly significant when considering the impact of climate change, which is associated with increased landslide and erosion susceptibility. The approach based on a national level presented in this work can provide valuable information for regional planning and decision-making processes.

Soil Erosion Under Climate and Land Use Changes in China: Incorporating Ecological Policy Constraints

ABSTRACTProjections of soil erosion under climate and land use changes are pivotal for optimizing soil conservation strategies. Ecological policies are thought to influence future land‐use changes and associated soil erosion dynamics. However, these policies are inadequately incorporated into projections, leaving the future trajectory of soil erosion still unclear. China's ecological redline policy (ERP) is among the first national policies to integrate multiple ecosystem services into land use planning, preventing anthropogenic soil erosion on over 25% of the territory. Therefore, focusing on China, three alternative Shared Socioeconomic Pathway and Representative Concentration Pathway scenarios (SSP1‐2.6, SSP3‐7.0, and SSP5‐8.5) were coupled with future‐oriented ERP to reflect future soil erosion patterns by the late‐21st century. Projections rely on an integrated multi‐model approach. The conducted analysis suggests that climate change is projected to exacerbate soil erosion by 12.06%–36.90% due to increased precipitation, characterized by high‐intensity events. Land use change is projected to mitigate or even reverse the climate‐induced increase in soil erosion. The combined climate and land use simulations showed that the annual average soil erosion rate will increase by 26.36% under the SSP5‐8.5 scenario, while it will decrease by 8.08% and 14.94% under the SSP1‐2.6 and SSP3‐7.0 scenarios, respectively. The implementation of ERP reduces potential soil erosion by 4.08%–14.89% (equal to 0.31–0.86 Gt year−1 soil loss) in the late‐21st century, particularly in scenarios with intensive conflicts between population and land sources. This study provides a valuable reference for the formulation of national strategies aimed at controlling soil loss accelerated by climate change.

Soil erosion risk in the Mocache Canton applying multicriteria analysis and geographic information systems

Soil erosion is one of the main and most widespread types of soil degradation, determined by environmental and anthropogenic factors, which significantly impact the physical, chemical and biological properties of the soil, favoring its degradation. Consequently, through this research we sought to evaluate the risk of soil erosion in the canton of Mocache through the application of multicriteria analysis techniques and the use of geographic information systems (GIS). The CORINE model included several criteria for the zoning of potential and actual erosion risk, including erosivity, defined by the Modified Fournier Index (MFI) and the Bagnouls-Gaussen Aridity Index (BGI); erodibility, composed of soil texture, stoniness and depth; soil occupation; slope-orientation; and vegetation cover, through the estimation of the Normalized Difference Vegetation Index (NDVI). An expert consultation supported by Analytic Hierarchy Process (AHP) was applied to define the contribution of each criterion to erosion risk. The resulting layers were combined using a weighted relationship (map algebra) within the GIS environment. It was obtained that slope-orientation and erosivity explain a large part of the erosion risk, with a weighting of 42.46% and 27.48% in order, according to the expert evaluation and the AHP. The high erosivity was contributed by the predominant climatic factors: intense precipitation and high temperatures. In addition, it was found that the potentialand current erosion risk represent 13.1% (7,244 ha) and 10.7% (5,905 ha) of the territorial extension. It is concluded that physical-natural, meteorological factors and anthropogenic activities contribute to the risk of potential and current soil erosion in Mocache canton

Cover crop grazing effects on soil properties in no-tillage dryland cropping systems in the central Great Plains

Integrating ruminant livestock such as beef cattle (Bos taurus L.) to graze cover crops (CCs) could balance goals of short-term profitability and long-term environmental sustainability when CCs are grown in water-limited environments like the central Great Plains (CGP), USA. However, little information currently exists about the effects of CC grazing on soil properties in no-tillage (NT) dryland cropping systems, especially after multiple cycles of grazing. This study was conducted from 2018 to 2021 to evaluate the effects of beef cattle grazing CCs on residue return, soil bulk density (BD) and penetration resistance (PR), water stable aggregates (WSA) and wind-erodible fraction (WEF), as well as soil pH and nutrient concentrations on three producer fields in central and western Kansas. Across sites, CC biomass left as residue post-grazing was similar to pre-grazing and was 60 % of the ungrazed CCs (3704 kg ha−1) because of CC regrowth after the 30–40 day grazing period. Soil BD, PR, WSA, WEF, pH, particulate organic carbon, nitrate-nitrogen, and phosphorus concentration were not different between grazed and ungrazed CCs. However, soil organic carbon (SOC) stocks and potassium concentrations were greater with grazed CCs compared to ungrazed CCs possibly due to substantial CC residue retention following grazing coupled with manure and urine deposition. Regression and correlation analyses showed that increased SOC was associated with decreased soil BD and increased WSA, which suggests decreased soil erosion potential as well as possible improvements in water infiltration and underscores the importance of SOC for overall soil health in this water-limited environment. Based on these results, we conclude that grazing of CCs is a viable management option for producers to intensify NT dryland cropping systems to improve soil health and maintain or increase overall system profitability in the CGP. Longer (>3 years) grazing studies are needed, and results are likely to vary based on grazing animal stocking rate, categories, duration of grazing, and available CC biomass for grazing.

Assessing soil erosion through the implementation of the RUSLE model and geospatial technology in the Isser watershed, northern Algeria

ABSTRACT Soil erosion, triggered by rainfall and runoff, poses a significant challenge for Mediterranean countries, leading to sedimentation in dam reservoirs, decreased storage capacities, and reduced agricultural fertility. Among various erosion estimation models, the RUSLE equation stands out for its consistency and minimal data requirements. The present study aims to utilize geographic information systems (GIS) software to quantify and map soil loss in the Isser watershed in northern Algeria employing the RUSLE model to strategically plan development measures and prioritize actions to safeguard high-risk erosion areas. Implementing the RUSLE-GIS approach involves integrating multiple datasets, including precipitation, soil erodibility, topography, vegetation cover, and anti-erosion practices. By combining these factors, a comprehensive map depicting erosion rates is generated. The findings categorize potential soil erosion into six groups, ranging from very low to extremely high. They indicate that 61.5% of the Isser Basin faces erosion, varying from moderate to very high (>20 t ha−1 year−1). In addition, 25% of the total surface experiences erosion levels classified as high to very high (>50 t ha−1 year−1). This underscores the urgent need for anti-erosive measures. These measures aim to safeguard the basin's soils, extend the lifespan of existing dam reservoirs (Koudiet Acerdoune and Beni Amran), and preserve their water potential.

Practical Calculation of Diaphragm Wall Deflection using Plaxis 3D Software

In this article, the mathematical models within the Plaxis 3D software were used to simulate and assess the deflection of diaphragm walls, comparing with data collected from a real project. This scientific and effective approach is crucial, as analyzing and simulating the excavation stages before constructing diaphragm walls for underground levels becomes essential for controlling wall displacement and preventing potential soil erosion issues in the surrounding deep excavation, which could have serious consequences for neighboring structures. The numerical modeling results demonstrate that the deflection of the diaphragm wall varies inversely with its thickness, but this variation is relatively small and quite compatible with the observed data

Modelling, quantification and estimation of the soil water erosion using the Revised Universal Soil Loss Equation with Sediment Delivery Ratio and the analytic hierarchy process models

AbstractThis research used the Revised Universal Soil Loss Equation (RUSLE) with Sediment Delivery Ratio (SDR) model. The analytic hierarchy process (AHP) method, while also incorporating the use of a geographic information system (GIS) and remote sensing (RS) to predict the annual soil loss rate and spatialise the processes of water erosion at the scale of the Loukkos Watershed, Morocco. The RUSLE model and AHP parameters were estimated using RS data, and the erosion vulnerability zones were determined using GIS. We used five parameters, including precipitation erosivity, soil erodibility, slope length and steepness, vegetation cover, and soil erosion control practices in the RUSLE. For the AHP technique, we used seven geo‐environmental factors, including annual average precipitation, drainage density, lineament density, slope, soil texture, land use/land cover and landform maps. The results of RUSLE indicated that the average annual soil loss varied from 0 to 2388.27 . The total estimated annual potential soil loss was approximately 40 790 220.11 , and a sediment yield estimated by RUSLE‐SDR was 8 647 526.66 , equivalent to 6.65 Mm3. This value is very close to the measured value of 6.81 Mm3, for a difference of 0.16 Mm3. Furthermore, the results of the AHP indicate that the soil erosion potential index varies from 0 to 0.205315 . Overall, nearly 13.7% of the area suffered from severe soil erosion exceeding 50 . Approximately 80% of the Loukkos Watershed area experienced only slight erosion, while the remaining 6% incurred moderate erosion. Integrating GIS and RS into the RUSLE model and AHP helped us robustly estimate the extent and degree of erosion risk. Territorial decision‐makers should adopt our results to develop soil conservation strategies, water management plans and other necessary soil and water conservation measures for this region.

Assessment of vegetation restoration impacts on soil erosion control services based on a biogeochemical model and RUSLE

Study regionLoess Plateau, China Study focusThe potential soil erosion has commonly been estimated using the revised universal soil loss equation (RUSLE) under bare land conditions. In few studies, biogeochemical models have been employed to simulate natural vegetation dynamics and assess the effects of regional vegetation restoration on soil loss control. In this study, a biogeochemical Biome-BGC (BBGC) model was developed to simulate the potential vegetation dynamics. The soil erosion rate and erosion control indices under both the current land use/cover (A, ERI) and the potential vegetation conditions (A’, ERI’) were estimated using the RUSLE model and an index-based ecosystem service approach, respectively. The effects of vegetation restoration on erosion control services were ultimately evaluated. New hydrologic insights for the regionThe BBGC model performed well in simulating the potential vegetation dynamics. The average annual soil retention increased by 84% after vegetation restoration since 1999. The increased erosion control services accounted for 62% of the Loess Plateau. Erosion control services increased to a high degree (ERI-ERI’ >0.4) in the southeast. Our results demonstrated that vegetation restoration effectively improved the erosion control services on the Loess Plateau. The results could provide a guidance in quantifying the regional effects of vegetation restoration on ecohydrological services and protecting the soil conservation function of watershed ecosystems.

Geoinformatics-Based Mapping of Environmental Sensitive Areas for Desertification over Satara and Sangli Districts of Maharashtra, India

Desertification processes in arid, semi-arid, and dry sub-humid conditions have been enhanced in recent decades. The geospatial database and associated satellite data can be effectively employed for regional planning to address desertification and land degradation. In this study, the Mediterranean Desertification and Land Use (MEDALUS) model has been used to map environmentally sensitive areas due to desertification in the Satara and Sangli districts of Maharashtra, India. This was achieved by combining Landsat-8 multispectral data, Census data, soil data, and climatic variables like temperature, rainfall, and evapotranspiration. The algorithm of MEDALUS is the geometric mean of four indicators, namely soil quality index (SQI), climate quality index (CQI), vegetation quality index (VQI), and socio-economic quality index (SEQI). The findings indicated that the majority of the study area comes under the potential category of desertification (60.32%) followed by fragile (27.87%) and critical (11.81%). Areas with a high propensity for desertification were found over the low to very low climatic quality and moderate to high soil quality including lower socio-economic quality. The lower socio-economic quality is mainly due to high to very high population density (>100 people/km2), low to moderate illiteracy rate (<16%), and low to moderate work participation rate (<50%) that incentivize unsustainable land use practices. The study provides a valuable tool for understanding and managing natural resources. It offers a detailed analysis of the environmental sensitivity of the study area, taking into account various factors like land use, vegetation cover, slope, and soil erosion potential. The developed comprehensive map of the area helps in identifying the most sensitive regions and developing appropriate conservation strategies. The information obtained from the study can be utilized to develop and implement successful measures to prevent or alleviate desertification, which is crucial for sustaining the health of ecosystems and the welfare of local residents.

Soil structure effect on soil erosion potential

Soil erosion poses a significant threat to water-related infrastructure such as bridges, dams, quays, and levees by detaching and transporting soil grains downstream, thereby compromising the structural support of these installations. While erosion damage is acknowledged in current design practices, understanding soil erosion parameters requires scrutiny. However, existing soil erosion databases mainly rely on reconstituted soil samples, which may differ substantially from in situ erosion due to alterations in soil structure. This study scrutinizes and contrasts the erodibilities of in situ and reconstituted soils. In situ soil samples were obtained using thin-walled Shelby tubes from Victoria, Canada, while reconstituted specimens were prepared in a slurry state and consolidated to match the overburden pressure on-site. A custom rotational erosion testing apparatus facilitated erosion testing on both Shelby tube and reconstituted specimens. The findings shed light on the influence of soil fabric on soil erosion potential, an aspect currently lacking in comprehensive understanding.

Geoinformatics and RUSLE model-based soil erosion assessment in a tropical mountainous area of Chite watershed, Mizoram, India

Soil erosion remains a persistent menace to the sustainability of agriculture and the environment in tropical mountainous regions. Soil erosion assessment is therefore necessary to identify degraded land areas for implementing effective conservation and management strategies. Hence, this study focuses on estimating potential soil erosion and analyzing their spatial patterns in the Chite watershed, situated in the Eastern Himalayas, India, using the Revised Universal Soil Loss Equation (RUSLE) model in Geographic Information System (GIS) platform. Various datasets encompassing remote sensing, ground observations, and laboratory analysis were employed to prepare the model’s input factors. The estimated mean erosion rate of the study area is 6.10 t ha-1 year-1, which produces a total soil loss of about 357580.90 t year-1. Spatial analysis reveals that about 5.79% of the watershed is under a relatively severe erosion category, contributing 70.13% of the total soil loss. Soil erosion appraisal with respect to the land use/ land cover (LULC) indicates a considerable consequence of various anthropogenic activities in the watershed. Higher rates of soil erosion are mainly observed on the bare land, cropland, and settlement areas which are characterized by steep and continuous slopes. The present findings were also validated with previous work undertaken in some comparable regions. This research can serve as a reliable tool towards the development of successful soil conservation measures and for promoting sustainable land use planning in this ecologically sensitive tropical mountainous region.

A statistical-based geospatial approach to prioritize the watersheds for soil erosion conservation in the Upper Awash Basin (Upstream Koka), Ethiopia

The current study focuses on the Upper Awash basin's morphometric parameters to understand the watershed's hydrologic characters with respect to soil erosion conservation. A correlation analysis based on a weighted sum approach was adopted to address the objectives of this research. The drainage patterns were extracted from SRTM-DEM (Shuttle Radar Topography Mission-digital elevation model), and ‘Stahler’s method’ was adopted to determine the stream order. The standardized formulas were employed to calculate about 23 different morphometric parameters. The Upper Awash basin (Koka) has been classified into six watersheds (WS-1 to WS-6). There are eleven selected variables, namely bifurcation ratio (Rb), drainage/stream frequency (Fs), drainage density (Dd), texture ratio (T), drainage texture (If), length of overland flow (Lo), form factor (Ff), shape factor (Bs), elongation ratio (Re), compact coefficient (CC) and circularity ratio (Rc) were used for prioritization ranking and categorization. The study has inferred four categories: very high, high, medium, and low, using the quartile statistical method and weighted compound value. Soil erosion is a major concern in watersheds composed of weak igneous rocks such as ignimbrite and holocene sediments such as limestone, conglomerate, sand, silt, and clay. Hence, three watersheds (WS-4, WS-5, and WS-6) with 53 % of the area have been identified as having strong soil erosion potential, representing very high and high categories requiring immediate conservation measures. Soil erosion conservation efforts and water resource management initiatives will benefit greatly from this effort. In addition, this study confirms that environmental studies utilizing a statistical approach based on GIS (geographical information system) are highly beneficial.

Assessment of sediment transport in Luxiapuqu watershed using RUSLE-TLSD and InSAR techniques: Yarlung Tsangpo River, China.

The Yarlung Tsangpo River Basin is characterized by its intricate topography and a significant presence of erosive materials. These often coincide with heavy localized precipitation, resulting in pronounced hydraulic erosion and geological hazards in mountainous regions. To tackle this challenge, we integrated the RUSLE-TLSD (Revised Universal Soil Loss Equation-Transportation-limited sediment delivery) model with InSAR (Interferometric Synthetic Aperture Radar) data, aiming to explore the sediment transport process and pinpoint hazard-prone sites within mountainous small watershed. The RUSLE-TLSD model aids in evaluating multi-year sediment transport dynamics in mountainous zones. And, the InSAR data precisely delineates changes in sediment scouring and siltation at sites vulnerable to hazards. Our research estimates that the potential average soil erosion within the watershed stands at 52.33 t/(hm2 a), with a net soil erosion of 0.69 t/(hm2 a), the sediment transport pathways manifest within the watershed's gullies and channels. Around 4.32% of the watershed area undergoes sedimentation, predominantly at the base of slopes and within channels. Notably, areas (d) and (e) emerge as the most susceptible to disasters within the watershed. Further analysis of the InSAR data highlighted four regions in the typical area (e) from 2017 that are either sedimentation- or erosion-prone, referred to as "hotspots." Among them, R1 exhibits a strong interplay between water and sediment, rendering it highly sensitive to environmental factors. In contrast, R4, characterized by a sharp bend in siltation, remains relatively impervious to external elements. The NDVI (normalized difference vegetation index) stands out as the pivotal determinant influencing sediment transport within the watershed, exerting a pronounced impact on the outlet section, especially in spring. By employing this approach, we gained a deeper understanding of sediment transport mechanisms and potential hazards in small watershed in uninformative mountainous areas. This study furnishes a robust scientific framework beneficial for erosion mitigation and disaster surveillance in mountainous watersheds.

Assessment of potential soil erosion in Mongolia based on the RUSLE model and RCP 8.5 scenario

AbstractDue to its relatively high altitude and a continental climate, environmental issues related to soil erosion and land degradation more seriously affect the ecosystem and crop production in Mongolia. As detailed soil erosion and land degradation assessments have only been performed in some regions of Mongolia, the purpose of this study is to evaluate the soil vulnerability on a national scale and predict future soil erosion under climate change prior to establishing an appropriate management plan. The revised universal soil loss equation model was chosen for this study, which reflects geographic and climatic characteristics in a vast area as the Mongolian territory. We evaluated soil erosion using historical data from 1993 and 2013 and generated predictions in the near (2041–2060) and far future (2061–2080) periods under the representative concentration pathway 8.5 scenario. The soil erosion rates were divided into six classes: very low, low, medium, high, very high and extreme. The total of 46,039 km2 of the Mongolian territory was classified as very high and extreme risk, which is predicted to increase up to 48,961 and 51,769 km2, in the near and far future periods, respectively. At the national scale, most of the soil erosion appeared in bare area, as it covers more than 60% of the total area. Meanwhile, the highest soil erosion risk was expected in high mountain ranges and ecologically vulnerable regions of the Gobi Desert and steppe area. This study identifies three land cover types with high priority for management and areas that should be considered first in the sustainable national land use and soil management plans considering regional characteristics.

SOIL EROSION AND IMPACT ON RECREATIONAL RESOURCES IN THE SHYNGYRLAU BASIN, WESTERN KAZAKHSTAN: A MULTI-ANALYTICAL ASSESSMENT

Over the past decades, water erosion has increased significantly in the Shyngyrlau River basin. Recreational development, haphazard construction and operation of roads have led to increased water erosion and the formation of numerous linear erosion forms. Erosion reduces the natural resource status of the region. Water erosion develops in most cases along roads laid along the thalwegs of the ravine-hollow network. The light substrate along with sparse vegetation cover (the sparseness is aggravated by intensive grazing) predetermine its rapid development. Water erosion is an acute problem arising from the present climate change, agricultural intensification and diverse forms of anthropogenic land degradation. Assessment of present and potential soil erosion is useful for landscape preservation as well as development planning. Multi-analytical modeling can provide a quantitative and consistent estimation of soil erosion and sediment yield under locally specific environmental conditions. The soil loss model, Revised Universal Soil Loss Equation (RUSLE), integrated with GIS, has been used to estimate soil loss in the Shyngyrlau Basin (a left-bank tributary of the Ural River, NW Kazakhstan). The RUSLE model is based on remote sensing and field data; erosion probabilities were determined using GIS. The percentage ratio of the soil loss in the Shyngyrlau River basin shows erosion variation of 0.001–2.47 t/ha/yr. The degree of erosion increases with the length of the slope. A new factor Chip curvature (Cu factor), defining the accuracy of the soil loss results, was defined. According to this factor, soil erosion in the study area is 0.007–2.48 t/ha/yr within the low erosion class. The lowest indicator of the K factor is 0.2 in sandy clay soils used as pasturelands. The highest K factor (0.3) relates to clayey arable soils. The research results add to implementation of new strategies in soil management and conservation practices reducing soil erosion in the Shyngyrlau Basin. Both climate and anthropogenic factors are seen behind the activated ground erosion. The development of forms of water erosion leads to a violation of the integrity of modern natural complexes of the West Kazakhstan region, which significantly reduces their stability and recreational potential.

Modeling of soil erosion risk in a typical tropical savannah landscape

Tropical savannah landscapes are faced with high soil degradation due to climate change and variability coupled with anthropogenic factors. However, the spatiotemporal dynamics of this is not sufficiently understood particularly, in the tropical savannah contexts. Using the Wa municipality of Ghana as a case, we applied the Revised Universal Soil Loss Equation (RUSLE) model to predict the potential and actual soil erosion risk for 1990 and 2020. Rainfall, soil, topography and land cover data were used as the input parameters. The rate of predicted potential erosion was in the range of 0–111 t ha−1yr−1 and 0–83 t ha−1yr−1 for the years 1990 and 2020, respectively. The prediction for the rate of potential soil erosion risk was generally higher than the actual estimated soil erosion risk which ranges from 0 to 59 t ha−1yr−1 in 1990 and 0 to 58 t ha−1yr−1 in 2020. The open savannah areas accounted for 75.8 % and 73.2 % of the total soil loss in 1990 and 2020, respectively. The validity of the result was tested using in situ data from a 2 km2 each of closed savannah, open savannah and settlement area. By statistical correlation, the predicted soil erosion risk by the model corresponds to the spatial extent of erosion damages measured in the selected area for the validation. Primarily, areas with steep slopes, particularly within settlement, were identified to have the highest erosion risk. These findings underscore the importance of vegetation cover and effective management practices in preventing soil erosion. The results are useful for inferences towards the development and implementation of sustainable soil conservation practice in landscapes with similar attributes.

Soil Erosion Risk Assessment in The Niğde Using Corine Model

Soil erosion risk was calculated using the coordination of information on the environment (CORINE) model in this study. The aim of the study is to determine the soil erosion risk of Niğde province, taking into account soil properties, slope and land use. Potential (PSER) and actual soil erosion risks (ASER) were determined using factors which were soil properties, slope, climatic factors, and land cover data. Data were produced using Arc-GIS 10.3 software, and results were obtained on these maps. 34.72% of the soils were classified as moderately actual soil erosion risk, which located in the eastern and southeast part of the study area.51.66% and 13.62% of the soils were classified as low and high actual soil erosion risk, respectively. Areas which have low actual soil erosion risk are located in the middle part, and areas which have high actual soil erosion risk are located in the northwest part of the area. The areas which were categorized as low potential soil erosion risk were increased from 23.52% to 51.66% in the actual soil erosion risk, after combining the land cover map. On the other hand, the total areas classified as high and moderate actual soil erosion risk decreased from 76.48% to 48.34% in the actual soil erosion risk due to land cover types. Soil texture, land cover, and slope are the most important factors that affect erosion risk. This study indicated that the CORINE model integrated with GIS (Geographic Information Systems) and RS (Revised Universal Soil Loss Equation) has a very effective and accurate potential for soil erosion risk assessment.

Soil Erosion Risk Assessment Using Corine Model: A Case Study in Shwan Sub basin, Kirkuk, Iraq

Water erosion is one of the most important problems and challenges facing the optimal management of natural resources, especially soil and water resources, because of its impact on soil degradation. This study aimed to classify the risk of soil water erosion and clarify its distribution in the Shwan Basin in Kirkuk Governorate - Iraq based on the Corine model.In the first stage of the work, the soil erodibilty, erosivity and slope factors were determined, classified and mapped according to the degree of their impact on soil erosion.The potential soil erosion risk map was prepared using Arc GIS 10.4.1.In the second stage, the land cover factor was calculated and classified according to the degree of protection. In the last stage, the actual soil erosion risk map was prepared by multiplying the class of land cover with the map of potential soil erosion risk over the entire study area.The study showed that 28.18% of the studied area is classified under a high risk, 39.57% represents as a medium risk and 32.25% is a low risk .The areas of severe soil erosion risk were concentrated in the southwestern part and some northern and central parts, and the areas of medium risk were concentrated in the northern, central and southern parts, while regarding the low actual risk, they were concentrated in the western parts and in random areas in the center and east of the study area.The results also showed that the Corine model for soil water erosion risk mapping is a highly effective and cost-effective approach.

Spatio-temporal variation in soil erosion on sloping farmland based on the integrated valuation of ecosystem services and trade-offs model: A case study of Chongqing, southwest China

Mastering the spatio-temporal evolution of soil erosion on regional sloping farmland is crucial for optimizing erosion control planning and carrying out soil quality evaluations. To simulate the potential or net soil erosion on sloping farmland in Chongqing, China, this study analyzed the temporal and spatial variation features of soil erosion using the integrated valuation of ecosystem services and trade-offs (InVEST) model and other models. The InVEST model was applied to calculate the soil erosion modulus on sloping farmland, hotspot analysis was used to identify hot and cold spots of sloping farmland erosion, and the chord diagram visualization model was used to reflect the transformation quantity and flow direction relationship between different erosion levels of sloping farmland transfer processes in different periods. The results showed that soil erosion on sloping farmland in Chongqing presents a distribution pattern of high values of soil erosion in the northeast and low values in the southwest. Very strong and severe erosion is concentrated in the low mountainous hilly areas in the northeast and southeast of Chongqing, while slightly and lightly eroded areas are distributed in the western and central flatter areas. The soil erosion grade of most sloping farmland is light and middle; in addition, the annual average soil erosion modulus shows a decreasing trend. Only in 2000 was it in the middle erosion grade. The areas with strong, very strong and severe erosion showed a downward trend, with the proportion decreasing from 18 % to 11 %. The average erosion modulus with slope > 25° was the largest (7553 t·km−2·a-1) and presented strong erosion. Soil erosion in sloping farmland mainly occurs between 400 and 1600 m of elevation. This research can effectively improve soil erosion control and quality control of sloping farmland and provide a reference for the sustainable development of land use in the region.

Determination of the potential soil losses and prioritization of sub-watersheds: Insight from North African highland system

Soil erosion has negative effects on people and property, hinders the sustainable development of natural resources, and poses a threat to the economic growth of territories worldwide, and is particularly acute for African countries. Consequently, identifying and prioritizing areas susceptible to this phenomenon is crucial for the implementation of efficient preventative measures. In this study, the empirical Erosion Potential Method (EPM) was used to quantify soil losses, and two Game Theory (GT) algorithms (Borda and Condorcet) were employed to identify locations prone to soil erosion and prioritize sub-watershed (SW) based on hydromorphometric characteristics in a hydrological system from High Atlas in Morocco. For this purpose, 26 factors were calculated, subsequently, a linear correlation analysis was conducted to assess the relationship between potential soil erosion and various influencing factors. The EPM model findings indicated average loss rates of roughly 3356 m3/km2/year, which are corroborated by 217 inventory points gathered in the most productive sediment locations, with an AUC value of 80 %. The results of prioritization using GT algorithms show that the SW6 and SW8 are classified as areas with high vulnerability to soil erosion, and the sub-watersheds located upstream of the Lakhdar river watershed are the units that deserve prioritization in terms of planning intervention. The validation of results indicates that the Borda algorithm performed better (AUC= 92 %) than the Condorcet algorithm (AUC= 72 %). This innovative approach enhances our understanding of erosive processes within specific spatial units, enabling informed decision-making and making a substantial contribution to the sustainable and efficient management of water resources. This represents a significant advancement compared to previous studies in the region.