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

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.

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Spatial Estimation of Soil Erosion Using RUSLE Modeling: A case study of Dolakha District, Nepal

10.21203/rs.3.rs-25478/v2 ◽

2020 ◽

Cited By ~ 1

Author(s):

Pawan Thapa

Keyword(s):

Land Use ◽

Soil Erosion ◽

Soil Loss ◽

Agricultural Land ◽

Management Planning ◽

Erosion Risk ◽

Spatial Estimation ◽

Soil Erosion Rate ◽

Severe Erosion ◽

Planning Processes

Abstract Background: In the mountainous areas, soil erosion causes the topsoil loss which decreases fertility in the agricultural land. Spatial estimation of soil erosion essential for an agriculture-dependent country like Nepal for developing erosion control plans. This study was conducted for estimation of soil erosion impacts on Dolakha using the Revised Universal Soil Loss Equation (RUSLE) model, also analyzes the effect of Land Use and Land Cover (LULC) on soil erosion.Results: The soil erosion rate had been categorized into 6 erosion classes based on the erosion severity, and 5.01% of the areas was found to be under extreme severe erosion risk (> 80 Mg ha-1yr-1) that should be addressed by decision-maker for reducing its rate and consequences. Followed by 10 % areas were classified under high to severe with the rate of soil loss range from 10 to 80 Mg ha-1yr-1. While 15% and 70% of areas remained in moderate and low-risk zone respectively. The results suggest this district northeastern part suffers from a high soil erosion risk due to steep slope.Conclusions: The result produces a spatial distribution of soil erosion over Dolakha, which can be applied for conservation and management planning processes, at the policy level, by land-use planners and decision-makers.

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Spatial Estimation of Soil Erosion Using RUSLE Modeling: A case study of Dolakha District

10.21203/rs.3.rs-25478/v1 ◽

2020 ◽

Author(s):

Pawan Thapa

Keyword(s):

Land Use ◽

Soil Erosion ◽

Soil Loss ◽

Agricultural Land ◽

Management Planning ◽

Erosion Risk ◽

Spatial Estimation ◽

Soil Erosion Rate ◽

Severe Erosion ◽

Planning Processes

Abstract Background: Soil erosion is one of the major causes of the topsoil loss, that decreases fertility in the agricultural land of a mountainous region. Spatial estimation of soil erosion is necessary for an agriculture-dependent country like Nepal for preparing erosion control plans. The purpose of this study was to estimate soil erosion of Dolakha using the Revised Universal Soil Loss Equation (RUSLE) model, which analyzes the effect of Land Use and Land Cover (LULC) and slope exposition on soil erosion.Results: The soil erosion rate had been categorized into 6 erosion classes based on the erosion severity, and 5.01% of the areas was found to be under extreme severe erosion risk (> 80 Mg ha-1yr-1) that need to address by decision-maker for reducing the risk of erosion. Followed by 10 % areas were classified under high to severe with rate of soil loss range from 10 to 80 Mg ha-1yr-1. While 15% and 70% areas were still remain in moderate and low risk zone respectively. The study demonstrated the northeastern part of district suffer high soil erosion risk due to steep slope and rugged landforms.Conclusions: The result produce spatial distribution of soil erosion over Dolakha, which can be applied for conservation and management planning processes, at the policy level, by land use planners and decision-makers.

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Spatial Estimation of Soil Erosion Using RUSLE Modeling: A case study of Dolakha District, Nepal

10.21203/rs.3.rs-25478/v4 ◽

2020 ◽

Author(s):

Pawan Thapa

Keyword(s):

Land Use ◽

Soil Erosion ◽

Agricultural Land ◽

Decision Makers ◽

Management Planning ◽

Erosion Risk ◽

Spatial Estimation ◽

The North ◽

Soil Erosion Rate ◽

Severe Erosion

Abstract Background: Soil erosion causes topsoil loss, which decreases fertility in agricultural land. Spatial estimation of soil erosion essential for an agriculture-dependent country like Nepal for developing its control plans. This study evaluated impacts on Dolakha using the Revised Universal Soil Loss Equation (RUSLE) model; analyses the effect of Land Use and Land Cover (LULC) on soil erosion. Results: The soil erosion rate categorized into six classes based on the erosion severity, and 5.01% of the areas found under extreme severe erosion risk (> 80 Mg ha-1yr-1) addressed by decision-makers for reducing its rate and consequences. Followed by 10 % classified between high and severe range from 10 to 80 Mg ha-1yr-1. While 15% and 70% of areas remained in a moderate and low-risk zone, respectively. Result suggests the area of the north-eastern part suffers from a high soil erosion risk due to steep slope. Conclusions: The result produces a spatial distribution of soil erosion over Dolakha, which applied for conservation and management planning processes, at the policy level, by land-use planners and decision-makers.

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

Environmental Sciences Proceedings ◽

10.3390/ecas2021-10348 ◽

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.

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Spatial Estimation of Soil Erosion Using RUSLE Modeling: A case study of Dolakha District, Nepal

10.21203/rs.3.rs-25478/v3 ◽

2020 ◽

Author(s):

Pawan Thapa

Keyword(s):

Land Use ◽

Soil Erosion ◽

Agricultural Land ◽

Decision Makers ◽

Management Planning ◽

Erosion Risk ◽

Spatial Estimation ◽

The North ◽

Soil Erosion Rate ◽

Severe Erosion

Abstract Background: Soil erosion causes topsoil loss, which decreases fertility in agricultural land. Spatial estimation of soil erosion essential for an agriculture-dependent country like Nepal for developing its control plans. This study evaluated impacts on Dolakha using the Revised Universal Soil Loss Equation (RUSLE) model; analyses the effect of Land Use and Land Cover (LULC) on soil erosion.Results: The soil erosion rate categorized into six classes based on the erosion severity, and 5.01% of the areas found under extreme severe erosion risk (> 80 Mg ha-1yr-1) addressed by decision-makers for reducing its rate and consequences. Followed by 10 % classified between high and severe range from 10 to 80 Mg ha-1yr-1. While 15% and 70% of areas remained in a moderate and low-risk zone, respectively. Result suggests the area of the north-eastern part suffers from a high soil erosion risk due to steep slope.Conclusions: The result produces a spatial distribution of soil erosion over Dolakha, which applied for conservation and management planning processes, at the policy level, by land-use planners and decision-makers.

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Application of the Adapted Approach for Crop Management Factor to Assess Soil Erosion Risk in an Agricultural Area of Rwanda

Land ◽

10.3390/land10101056 ◽

2021 ◽

Vol 10 (10) ◽

pp. 1056

Author(s):

Albert Poponi Maniraho ◽

Richard Mind’je ◽

Wenjiang Liu ◽

Vincent Nzabarinda ◽

Patient Mindje Kayumba ◽

...

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Erosion Rate ◽

High Probability ◽

Crop Management ◽

Agricultural Area ◽

Erosion Risk ◽

Western Province ◽

Soil Erosion Risk ◽

Soil Erosion Rate

Land use and land cover (LULC) management influences the severity of soil erosion risk. However, crop management (C) is one factor of the Revised Universal Soil Loss Equation (RUSLE) model that should be taken into account in its determination, as it influences soil loss rate estimations. Thus, the present study applied an adapted C-factor estimation approach (CvkA) modified from the former approach (Cvk) to assess the impact of LULC dynamics on soil erosion risk in an agricultural area of Rwanda taking the western province as a case study. The results disclosed that the formerly used Cvk was not suitable, as it tended to overestimate C-factor values compared with the values obtained from t CvkA. An approximated mean soil loss of 15.1 t ha−1 yr−1, 47.4 t ha−1 yr−1, 16.3 t ha−1 yr−1, 66.8 t ha−1 yr−1 and 15.3 t ha−1 yr−1 in 2000, 2005, 2010, 2015 and 2018, respectively, was found. The results also indicated that there was a small increase in mean annual soil loss from 15.1 t ha−1 yr−1 in 2000 to 15.3 t ha−1 yr−1 in 2018 (1.3%). Moreover, the soil erosion risk categories indicated that about 57.5%, 21.8%, 64.9%, 15.5% and 73.8% had a sustainable soil erosion rate tolerance (≤10 t ha−1 yr−1), while about 42.5%, 78.2%, 35.1%, 84.5% and 16.8% had an unsustainable mean soil erosion rate (>10 t ha−1 yr−1) in 2000, 2005, 2010, 2015 and 2018, respectively. A major portion of the area fell under the high and very high probability zones, whereas only a small portion fell under the very low, low, moderate and extremely high probability zones. Therefore, the CvkA approach presents the most suitable alternative to estimate soil loss in the western province of Rwanda with reasonable soil loss prediction results. The study area needs urgent intervention for soil conservation planning, taking into account the implementation of effective conservation practices such as terracing for soil erosion control.

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Analysis of Ownership Data from Consolidated Land Threatened by Water Erosion in the Vlára Basin, Slovakia

Sustainability ◽

10.3390/su13010051 ◽

2020 ◽

Vol 13 (1) ◽

pp. 51

Author(s):

Alexandra Pagáč Mokrá ◽

Jakub Pagáč ◽

Zlatica Muchová ◽

František Petrovič

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Agricultural Land ◽

Water Erosion ◽

Land Consolidation ◽

Land Fragmentation ◽

Erosion Risk ◽

Definition Of ◽

The Relationship ◽

Soil Loss Equation

Water erosion is a phenomenon that significantly damages agricultural land. The current land fragmentation in Slovakia and the complete ambiguity of who owns it leads to a lack of responsibility to care for the land in its current condition, which could affect its sustainability in the future. The reason so much soil has eroded is obvious when looking at current land management, with large fields, a lack of windbreaks between them, and no barriers to prevent soil runoff. Land consolidation might be the solution. This paper seeks to evaluate redistributed land and, based on modeling by the Universal Soil Loss Equation (USLE) method, to assess the degree of soil erosion risk. Ownership data provided information on how many owners and what amount of area to consider, while taking into account new conditions regarding water erosion. The results indicate that 2488 plots of 1607 owners which represent 12% of the model area are still endangered by water erosion, even after the completion of the land consolidation project. The results also presented a way of evaluating the territory and aims to trigger a discussion regarding an unambiguous definition of responsibility in the relationship between owner and user.

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Assessment of Soil Erosion and Its Impact on Agricultural Productivity by Using the RMMF Model and Local Perception: A Case Study of Rangun Watershed of Mid-Hills, Nepal

Applied and Environmental Soil Science ◽

10.1155/2021/5747138 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Dinesh Bhandari ◽

Rajeev Joshi ◽

Raju Raj Regmi ◽

Nripesh Awasthi

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Group Discussion ◽

Agricultural Productivity ◽

Weighted Mean ◽

Risk Area ◽

Barren Land ◽

Erosion Risk ◽

Risk Areas ◽

The Impact

Soil erosion is a major concern for the environment and natural resources leading to a serious threat to agricultural productivity and one of the major causes of land degradation in the mid-hills region of Nepal. An accurate assessment of soil erosion is needed to reduce the problem of soil loss in highly fragile mountainous areas. The present study aimed to assess spatial soil loss rate and identified risk areas and their perceived impact on agricultural productivity by using the Revised Morgan–Morgan–Finney (RMMF) model and social survey in the Rangun watershed of Dadeldhura district, Nepal. Soil erosion was assessed by using data on soil, digital elevation model, rainfall, land use, and land cover visually interpreted from multitemporal satellite images, and ILWIS 3.3 academic software was used to perform the model. A household questionnaire survey (n = 120) and focus group discussion (n = 2) in identified risk areas were carried out to understand the people’s perception towards soil erosion and its impact on agricultural productivity. The predicted average soil erosions from the forest, agriculture, and barren land were 2.7 t ha−1 yr−1, 53.73 t ha−1 yr−1, and 462.59 t ha−1 yr−1, respectively. The erosion risk area under very low to low, moderate to moderately high, and high to very high covers 92.32%, 4.96%, and 2.73%, respectively. It indicates that the rate of soil erosion was lower in forest areas, whereas it was higher in the barren land. The cropped area of the watershed has been reduced by 2.96 ha−1 yr−1, and productivity has been decreased by 0.238 t ha−1 yr−1. The impacts such as removal of topsoil (weighted mean = 4.19) and gully formation (weighted mean = 3.56) were the highest perceived factors causing productivity decline due to erosion. People perceived the impact of erosion in agricultural productivity differently ( ∗ significant at P ≤ 0.05 ). The study concluded that, comparatively, barren and agricultural lands seem more susceptible to erosion, so the long-term conservation and management investment in susceptible areas for restoration, protection, and socioeconomic support contribute significantly to land rehabilitation in the Rangun watershed.

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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

ENVIRONMENTAL SYSTEMS RESEARCH ◽

10.1186/s40068-020-00203-3 ◽

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.

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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)

European Scientific Journal ESJ ◽

10.19044/esj.2018.v14n3p524 ◽

2018 ◽

Vol 14 (3) ◽

pp. 524 ◽

Cited By ~ 2

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).

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