scholarly journals Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India

2021 ◽  
Vol 8 (1) ◽  
pp. 26
Author(s):  
Manti Patil ◽  
Radheshyam Patel ◽  
Arnab Saha
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Crop Production ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Reservoir Sedimentation ◽  
Reservoir Water ◽  
Slope Length ◽  
Soil Erosion Rate

Soil erosion is one of the most critical environmental hazards of recent times. It broadly affects to agricultural land and reservoir sedimentation and its consequences are very harmful. In agricultural land, soil erosion affects the fertility of soil and its composition, crop production, soil quality and land quality, yield and crop quality, infiltration rate and water holding capacity, organic matter and plant nutrient and groundwater regimes. In reservoir sedimentation process the consequences of soil erosion process are reduction of the reservoir capacity, life of reservoir, water supply, power generation etc. Based on these two aspects, an attempt has been made to the present study utilizing Revised Universal Soil Loss Equation (RUSLE) has been used in integration with remote sensing and GIS techniques to assess the spatial pattern of annual rate of soil erosion, average annual soil erosion rate and erosion prone areas in the MAN catchment. The RUSLE considers several factors such as rainfall, soil erodibility, slope length and steepness, land use and land cover and erosion control practice for soil erosion prediction. In the present study, it is found that average annual soil erosion rate for the MAN catchment is 13.01-tons/ha/year, which is higher than that of adopted and recommended values for the project. It has been found that 53% area of the MAN catchment has negligible soil erosion rate (less than 2-tons/ha/year). Its spatial distribution found on flat land of upper MAN catchment. It has been detected that 26% area of MAN catchment has moderate to extremely severe soil erosion rate (greater than 10-tons/ha/year). Its spatial distribution has been found on undulated topography of the middle MAN catchment. It is proposed to treat this area by catchment area treatment activity.

scholarly journals Modelisation Du Risque D’érosion Hydrique Par L’équation Universelle Des Pertes En Terre Dans Le Rif Occidental: Cas Du Bassin Versant De Moulay Bouchta (Maroc)

2018 ◽  
Vol 14 (3) ◽  
pp. 524 ◽  
Author(s):  
Anis Zouagui ◽  
Mohamed Sabir ◽  
Mustapha Naimi ◽  
Mohamed Chikhaoui ◽  
Moncef Benmansour
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Land Development ◽  
Principal Component ◽  
Slope Length ◽  
Increased Risk ◽  
Effect Of Support ◽  
Soil Losses

Soil erosion causes many environmental and socio-economic problems: loss of biodiversity, decrease in the productivity of agricultural land, siltation of dams and increased risk of flooding. It is therefore essential to establish a detailed evaluation of this process before any spatial planning. To evaluate the effects of soil erosion spatially and quantitatively in order to face this phenomenon, and propose the best conservation and land development strategies, the Universal Soil Loss Equation (USLE) coupled with a geographic information system (GIS) is applied. This model is a multiplication of the five erosion factors: the erosivity of the rain, the erodibility of the soil, the inclination and the slope length, the vegetation cover and the anti-erosion practices. The study area is the Moulay Bouchta watershed (7 889 ha), which is located in the western part of the Rif Mountains, is characterized by a complex and contrasting landscape. The resulting soil loss map shows an average erosion rate of 39.5 (t/ha/yr), 87% of the basin has an erosion rate above the tolerance threshold for soil loss (7 (t/ha/yr)). Soil losses per subbasin range from 16.2 to 81.4 (t/ha/yr). The amount of eroded soil is estimated at 311,591 (t/yr), corresponding to a specific degradation of 12.1 (t/ha/yr). In the absence of any erosion control, 25% of the soil losses would reach the new dam located a little upstream of the basin outlet, reducing its water mobilization capacity to 59,625 (m3/yr). The application of Principal Component Analysis (PCA) to soil erosion factors shows a significant influence of topographic factor (LS) on soil erosion process, followed by the effect of support practices (P), then by soil erodibility (K).

scholarly journals Estimation of Soil Erosion in Nepal Using a RUSLE Modeling and Geospatial Tool

Geosciences ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 147 ◽  
Author(s):  
Pooja Koirala ◽  
Sudeep Thakuri ◽  
Subesh Joshi ◽  
Raju Chauhan
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Entire Area ◽  
Barren Land ◽  
Erosion Risk ◽  
Soil Erosion Rate ◽  
Severe Erosion ◽  
The Mean

Soil erosion is a major issue, causing the loss of topsoil and fertility in agricultural land in mountainous terrain. Estimation of soil erosion in Nepal is essential because of its agriculture-dependent economy (contributing 36% to national GDP) and for preparing erosion control plans. The present study, for the first time, attempts to estimate the soil loss of Nepal through the application of the Revised Universal Soil Loss Equation (RUSLE) model. In addition, it analyzes the effect of Land Use and Land Cover (LULC) and slope ( β ) exposition on soil erosion. Nation-wide mean annual soil loss of Nepal is estimated at 25 t ha−1 yr−1 with a total of 369 million tonnes (mT) of potential soil loss. Soil erosion based on the physiographic region of the country shows that the Middle Mountains, High Mountains, High Himal, Chure, and Terai have mean erosion rates of 38.0, 32.0, 28.0, 7.0, and 0.1 t ha−1 yr−1. The soil erosion rate by basins showed that the annual erosions of the Karnali, Gandaki, Koshi, and Mahakali River basins are 135, 96, 79, and 15 mT, respectively. The mean soil erosion rate was significantly high (34 t ha−1 yr−1) for steep slopes (β > 26.8%) and the low (3 t ha−1 yr−1) for gentle slopes (β < 5%). Based on LULC, the mean erosion rate for barren land was the highest (40 t ha−1 yr−1), followed by agricultural land (29 t ha−1 yr−1), shrubland (25 t ha−1 yr−1), grassland (23 t ha−1 yr−1), and forests (22 t ha−1 yr−1). The entire area had been categorized into 6 erosion classes based on the erosion severity, and 11% of the area was found to be under a very severe erosion risk (> 80 t ha−1 yr−1) that urgently required reducing the risk of erosion.

scholarly journals Soil loss estimation and severity mapping using RUSLE model and GIS: a case study in Megech Watershed, Ethiopia

2022 ◽  
Author(s):  
Legese Abebaw Getu ◽  
Attila Nagy ◽  
Hailu Kendie Addis
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Risk Category ◽  
Model Parameters ◽  
Main Concern ◽  
Slope Length ◽  
Rusle Model ◽  
Soil Erosion Rate ◽  
Very High

Abstract AbstractBackground: Soil erosion is the most serious problem that affects economic development, food security, and ecosystem services which is the main concern in Ethiopia. This study focused on quantifying soil erosion rate and severity mapping of the Megech watershed for effective planning and decision-making processes to implement protection measures. The RUSLE model integrated with ArcGIS software was used to conduct the present study. The six RUSLE model parameters: erosivity, erodibility, slope length and steepness, cover management, and erosion control practices were used as input parameters to predict the average annual soil loss and identify erosion hotspots in the watershed. Results: The RUSLE estimated 1,399,210 tons yr-1 total soil loss from the watershed with a mean annual soil loss of 32.84 tons ha-1yr-1. The soil erosion rate was varied from 0.08 to greater than 500 tons ha-1yr-1. A severity map with seven severity classes was created for 27 sub-watersheds: low (below 10), moderate (10-20), high (20-30), very high (30-35), severe (35-40), very severe (40-45) and extremely severe (above 45) in which the values are in tons ha-1yr-1. The area coverage was 6.5%, 11.1%, 8.7%, 22%, 30.9%, 13.4%, and 7.4% for low, moderate, high, very high, severe, very severe, and extremely severe erosion classes respectively. Conclusion: About 82 % of the watershed was found in more than the high-risk category which reflects the need for immediate land management action. This paper could be important for decision-makers to prioritize critical erosion hotspot areas for comprehensive and sustainable management of the watershed.

scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

Spatial-based assessment of land use, soil erosion, and water protection in the Jeneberang valley, Indonesia

Biologia ◽  
2009 ◽  
Vol 64 (3) ◽  
Author(s):  
Sumbangan Baja ◽  
Muhamad Ramli ◽  
Syamsul Lias
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Land Degradation ◽  
Agricultural Land ◽  
Sustainable Land Use ◽  
Water Protection ◽  
Large Area ◽  
Soil Erosion Rate ◽  
Analytical Procedures

AbstractSoil erosion by water is considered as one of the most significant forms of land degradation that affects sustained productivity of agricultural land use and water quality. It is influenced by a considerable number of factors (including climate, soil, topography, land use and types of land management), so that the information on the spatial distribution of soil erosion rate and its related effects can be effectively employed as a baseline data for land use development and water protection. The principal aim of this study is three-fold: (i) to map existing land use; (ii) to assess and map the spatial distribution of average annual rate of soil losses in the study area; (iii) to evaluate spatial matching between existing and proposed land use including a distance analysis from the water body (the Bili-Bili Dam). An analytical procedures used, respectively, include supervised classification of satellite imagery, application of RUSLE (Revised USLE), and overlay analysis in a raster GIS environment, utilising available information in the region covering some parts of Jeneberang catchment, South Sulawesi, Indonesia. The results suggest that the outputs of this study can be used for the identification of land units on a cell-basis with different land use types, rate of soil loss, inconsistency between proposed and planned land use, as well as the threat of land degradation to the main river and the dam. The analytical procedures developed in this research may be useful in other areas, particularly in the studies related to the assessment and mapping of land use and erosion for the importance of sustainable land use at a relatively large area.

scholarly journals SPATIAL DISTRIBUTION OF SOIL LOSS IN UPPER DIDESSA WATERSHED, ETHIOPIA

2019 ◽  
Vol 4 (4) ◽  
pp. 434-443 ◽  
Author(s):  
Fayera Gudu Tufa ◽  
Tolera Abdissa Feyissa
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Agricultural Land ◽  
Nutrient Loss ◽  
Geographical Information ◽  
Water Supply Systems ◽  
Factor C ◽  
Soil Loss Rate

Soil erosion is dramatically increasing and accelerating in developing countries like Ethiopia. It has worrisome economic and environmental impacts and causes nutrient loss on agricultural land, sedimentation in rivers and reservoirs, clogged canals and other water supply systems. Determination of spatial distribution of soil loss rate in upper Didessa watershed is an important priority for prioritizing the area for watershed management practices in order to reduce soil erosion. The Revised Universal Soil Loss Equation (RUSLE) framed with geographical information system and remote sensing technique was used to estimate the mean annual soil loss in Upper Didessa Watershed, Ethiopia. Digital elevation model (DEM) with 30mx30m resolution was collected from Ministry of Water, Irrigation and Energy and used to delineate the watershed. Soil loss factors of the watershed like length and slope factor (LS), soil erodibility factor (K), cover management factor (C), support practicing factor (P) and rain fall erosivity factor (R) were evaluated and integrated in GIS to compute the annual soil loss rate of the watershed. The results of this work reveal that the annual rate of soil loss in the watershed is 5.23 t / ha / year. They also show that the central part of the watershed is an area prone to soil erosion. DISTRIBUIÇÃO ESPACIAL DA PERDA DO SOLO NA BACIA HIDROGRÁFICA SUPERIOR DIDESSA, ETIÓPIA ResumoA erosão do solo está aumentando e acelerando dramaticamente em países em desenvolvimento como a Etiópia. Tem impactos econômicos e ambientais preocupantes e causa perda de nutrientes em terras agrícolas, sedimentação em rios e reservatórios, entupimento de canais e outros sistemas de fornecimento de água. A determinação da distribuição espacial da taxa de perda de solo na bacia hidrográfica superior do Rio Didessa é uma prioridade importante para priorizar a área para práticas de manejo de bacias hidrográficas a fim de reduzir a erosão do solo. A Equação Universal de Perda de Solo Revisada (RUSLE), enquadrada com sistema de informação geográfica e técnica de sensoriamento remoto, foi usada para estimar a perda média anual de solo na Bacia do Alto Didessa, na Etiópia. O modelo digital de elevação (DEM) com resolução de 30mx30m foi coletado no Ministério da Água, Irrigação e Energia e utilizado para delinear a bacia hidrográfica. Os fatores de perda de solo da bacia hidrográfica, como comprimento e fator de inclinação (LS), fator de erodibilidade do solo (K), fator de manejo da cobertura (C), fator de prática de apoio (P) e fator de erosividade da chuva (R) foram avaliados e integrados no SIG para calcular a taxa anual de perda de solo da bacia hidrográfica. Os resultados deste trabalho revelam que taxa anual de perda de solo da bacia hidrográfica é de 5,23 t / ha / ano. Mostram ainda que a parte central da bacia hidrográfica é uma área propensa à erosão do solo. Palavras-chave: SIG. Perda de solo. RUSLE. Didessa superior da bacia hidrográfica.

scholarly journals Sensitivity Assessment of Spatial Resolution Difference in DEM for Soil Erosion Estimation Based on UAV Observations: An Experiment on Agriculture Terraces in the Middle Hill of Nepal

2021 ◽  
Vol 10 (1) ◽  
pp. 28
Author(s):  
Chhabi Lal Chidi ◽  
Wei Zhao ◽  
Suresh Chaudhary ◽  
Donghong Xiong ◽  
Yanhong Wu
Keyword(s):  
High Resolution ◽  
Soil Erosion ◽  
Environmental Sustainability ◽  
Erosion Rate ◽  
Slope Gradient ◽  
Slope Length ◽  
Dem Resolution ◽  
Gradient Slope ◽  
Soil Erosion Rate ◽  
Sensitivity Assessment

Soil erosion in the agricultural area of a hill slope is a fundamental issue for crop productivity and environmental sustainability. Building terrace is a very popular way to control soil erosion, and accurate assessment of the soil erosion rate is important for sustainable agriculture and environmental management. Currently, many soil erosion estimations are mainly based on the freely available medium or coarse resolution digital elevation model (DEM) data that neglect micro topographic modification of the agriculture terraces. The development of unmanned aerial vehicle (UAV) technology enables the development of high-resolution (centimeter level) DEM to present accurate topographic features. To demonstrate the sensitivity of soil erosion estimates to DEM resolution at this high-resolution level, this study tries to evaluate soil erosion estimation in the Middle Hill agriculture terraces in Nepal based on UAV derived high-resolution (5 × 5 cm) DEM data and make a comparative study for the estimates by using the DEM data aggregated into different spatial resolutions (5 × 5 cm to 10 × 10 m). Firstly, slope gradient, slope length, and topographic factors were calculated at different resolutions. Then, the revised universal soil loss estimation (RUSLE) model was applied to estimate soil erosion rates with the derived LS factor at different resolutions. The results indicated that there was higher change rate in slope gradient, slope length, LS factor, and soil erosion rate when using DEM data with resolution from 5 × 5 cm to 2 × 2 m than using coarser DEM data. A power trend line was effectively used to present the relationship between soil erosion rate and DEM resolution. The findings indicated that soil erosion estimates are highly sensitive to DEM resolution (from 5 × 5 cm to 2 × 2 m), and the changes become relatively stable from 2 × 2 m. The use of DEM data with pixel size larger than 2 × 2 m cannot detect the micro topography. With the insights about the influencing mechanism of DEM resolution on soil erosion estimates, this study provides important suggestions for appropriate DEM data selection that should be investigated first for accurate soil erosion estimation.

scholarly journals Assessment of Soil Erosion by the RUSLE Model Using Remote Sensing and GIS: A Case Study of Jilin Province of China

2020 ◽  
Author(s):  
Ping ZHOU ◽  
Yajin GE ◽  
Yue JIANG ◽  
Yanan XIE ◽  
Zhiwen SI ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Food Production ◽  
Erosion Rate ◽  
Slope Angle ◽  
Jilin Province ◽  
Rusle Model ◽  
Soil Erosion Rate

The accurate assessment and monitoring of soil erosion is of great significance for guiding food production and ensuring ecological security, and it is a current research hotspot. In this paper, remote sensing and geographic information systems (GISs) are combined with the Revised Universal Soil Loss Equation (RUSLE model) to carry out research on soil erosion monitoring and make a quantitative evaluation. According to five factors, including rainfall erosivity, soil erodibility, topography, vegetation cover, crop management and water and soil conservation measures, the distribution of the soil erosion rate in Jilin Province in 2019 was mapped, and the soil erosion rate was divided into 5 levels according to the degree of erosion, including very slight, slight, moderate, severe and extremely severe erosion. Based on the segmented S-slope factor model and the unique topographical features of the study area, the relationships among the soil erosion rate, erosion risk level, erosion area, erosion amount and slope angle (θ) were systematically analysed, and a slope angle of 15° was identified as the threshold for soil erosion on sloped farmland in Jilin Province. The total soil erosion in Jilin Province was 402.14×106 t in 2019, the average soil erosion rate was 21.6 t·ha-1·a-1, and the average soil loss thickness was 1.6 mm·a-1; these values were far greater than the soil erosion rate risk threshold of 10 t ·Ha-1·a-1. Thus, the province has a strong level of soil erosion. We conclude that soil degradation is accelerating, and food production and the ecological environment will face severe challenges. It is suggested that soil erosion control should be carried out according to different types and slopes of land, with an emphasis on the management of forestland and farmland because forestland and farmland are currently the first types of land to be managed in Jilin Province. This paper aims to explore a timely, fast, efficient and convenient soil erosion monitoring and evaluation method and provide effective monitoring tools for agricultural water and soil conservation, ecological safety management and stable food production in Jilin Province and similar black soil areas.

scholarly journals The overshadow of the human evolvement process in the dynamics of soil drift of an agricultural watershed in Nilgiri Hills, India

2021 ◽  
Author(s):  
Sangeetha Ramakrishnan ◽  
Ambujam Neelakanda Pillai Kanniperumal
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Agricultural Watershed ◽  
Rainfall Erosivity ◽  
Landsat Images ◽  
Slope Length ◽  
Data Format ◽  
Conservation Practice ◽  
Soil Erosion Rate ◽  
Agricultural Planning

The Nilgiri Biosphere, being one of the critical catchments, a small agricultural watershed of Udhagamandalam has been analysed to show the need to improve the agriculture by reducing the soil erosion. For this study, the land use and land cover classification was undertaken using Landsat images to highlight the changes that have occurred between 1981 and 2019. The Revised Universal Soil Loss Equation (RUSLE) method and the Geographic Information System (GIS) was used in this study to determine the soil erosion vulnerability of Sillahalla watershed in the Nilgiri Hills in Tamilnadu. This study will help to promote the economic development of the watershed with proper agricultural planning and erosion management. This study focuses on the estimation of the average annual soil loss and to classify the spatial distribution of the soil loss as a map with the RUSLE method and GIS. To estimate the average annual soil loss of the study area, GIS layers of the RUSLE factors like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C) and conservation practice (P) were computed in a raster data format. The total soil loss and average annual soil loss of the study area for 1981–1990,1991–2000, 2001–2010, 2011–2019 were found to be 0.2, 0.254, 0.3, 0.35 million t/year and 31.33, 37.78, 46.7, 51.89 t/ha/year, respectively. The soil erosion rate is classified into different classes as per the FAO guidelines and this severity classification map was prepared to identify the vulnerable areas.

scholarly journals Assessment of Soil Erosion at Multiple Spatial Scales Following Land Use Changes in 1980-2017 in the Black Soil Region, (NE) China

2020 ◽  
Author(s):  
Haiyan Fang ◽  
Zemeng Fan
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Spatial Scales ◽  
Land Use Changes ◽  
Arable Land ◽  
Rainfall Erosivity ◽  
Erosion Rates ◽  
Soil Erosion Rate

Impact of land use and land cover (LULC) change on soil erosion is still imperfectly understood, especially in northeastern China (NEC). Based on the Revised Universal Loss Equation (RUSLE), the variability of soil erosion at different spatial scales following land use changes in1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 t ha-1 yr-1 with an average of 4.22 t ha-1 yr-1 in 1980-2017. The rates of soil erosion less than 1.41 t ha-1 yr-1 decreased from 1980 to 2010, and increased from 2010 to 2017, and opposite changing patterns occurred in higher erosion classes (i.e., above 5 t ha-1 yr-1). At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 t ha-1 yr-1, followed by Jilin Province, the east Inner Mongolia, and Heilongjing Province. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 t ha-1 yr-1. At a county scale, around 75% of the countries had soil erosion rate higher than its tolerance level. The county numbers with higher erosion rate increased in 1980-2010 and decreased in 2010- 2017, resulting from the sprawl and withdrawal of arable land. The results indicate that appropriate policies can control soil loss through limiting arable land sprawl in areas of unfavorable regions in the NEC.

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