scholarly journals Geomorphic Control on Soil Erosion – a Case Study in the Subarnarekha Basin, India

2021 ◽  
Vol 54 (1) ◽  
pp. 1
Author(s):  
Amar Kumar Kathwas ◽  
Nilanchal Patel
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Principal Component ◽  
Soil Surface ◽  
Distant Location ◽  
The Individual ◽  
Degree Of Association ◽  
Soil Erosion By Water ◽  
Qualitative And Quantitative Characteristics

<p>Geomorphology depicts the qualitative and quantitative characteristics of both terrain and landscape features combined with the processes responsible for its evolution. Soil erosion by water involves processes, which removes soil particles and organic matter from the upper sheet of the soil surface, and then transports the eroded material to distant location under the action of water. Very few studies have been conducted on the nature and dynamics of soil erosion in the different geomorphologic features. In the present investigation, an attempt has been made to assess the control of geomorphologic features on the soil loss. Universal Soil Loss Equation (USLE) was used to determine soil loss from the various geomorphological landforms. Principal component analysis (PCA) was implemented on the USLE parameters to determine the degree of association between the individual principal components and the USLE-derived soil loss. Results obtained from the investigation signify the influence of the various landforms on soil erosion. PC5 is found to be significantly correlated with the USLE-derived soil loss. The results ascertained significant association between the soil loss and geomorphological landforms, and therefore, suitable strategies can be implemented to alleviate soil loss in the individual landforms.</p>

scholarly journals A comparison between soil loss evaluation index and the C-factor of RUSLE: a case study in the Loess Plateau of China

2012 ◽  
Vol 16 (8) ◽  
pp. 2739-2748 ◽  
Author(s):  
W. W. Zhao ◽  
B. J. Fu ◽  
L. D. Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Drainage Network ◽  
Land Use Patterns ◽  
Low Area ◽  
Use Patterns ◽  
High Area ◽  
Land Use Types

Abstract. Land use and land cover are most important in quantifying soil erosion. Based on the C-factor of the popular soil erosion model, Revised Universal Soil Loss Equation (RUSLE) and a scale-pattern-process theory in landscape ecology, we proposed a multi-scale soil loss evaluation index (SL) to evaluate the effects of land use patterns on soil erosion. We examined the advantages and shortcomings of SL for small watershed (SLsw) by comparing to the C-factor used in RUSLE. We used the Yanhe watershed located on China's Loess Plateau as a case study to demonstrate the utilities of SLsw. The SLsw calculation involves the delineations of the drainage network and sub-watershed boundaries, the calculations of soil loss horizontal distance index, the soil loss vertical distance index, slope steepness, rainfall-runoff erosivity, soil erodibility, and cover and management practice. We used several extensions within the geographic information system (GIS), and AVSWAT2000 hydrological model to derive all the required GIS layers. We compared the SLsw with the C-factor to identify spatial patterns to understand the causes for the differences. The SLsw values for the Yanhe watershed are in the range of 0.15 to 0.45, and there are 593 sub-watersheds with SLsw values that are lower than the C-factor values (LOW) and 227 sub-watersheds with SLsw values higher than the C-factor values (HIGH). The HIGH area have greater rainfall-runoff erosivity than LOW area for all land use types. The cultivated land is located on the steeper slope or is closer to the drainage network in the horizontal direction in HIGH area in comparison to LOW area. The results imply that SLsw can be used to identify the effect of land use distribution on soil loss, whereas the C-factor has less power to do it. Both HIGH and LOW areas have similar soil erodibility values for all land use types. The average vertical distances of forest land and sparse forest land to the drainage network are shorter in LOW area than that in HIGH area. Other land use types have shorter average vertical distances in HIGH area than that LOW area. SLsw has advantages over C-factor in its ability to specify the subwatersheds that require the land use patterns optimization by adjusting the locations of land uses to minimize soil loss.

scholarly journals A Remote Sensing Based Method to Detect Soil Erosion in Forests

2019 ◽  
Vol 11 (5) ◽  
pp. 513 ◽  
Author(s):  
Hanqiu Xu ◽  
Xiujuan Hu ◽  
Huade Guan ◽  
Bobo Zhang ◽  
Meiya Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Southern China ◽  
Red Soil ◽  
Forest Area ◽  
Landsat 8 ◽  
Large Spatial Scale ◽  
Five Factors

Rainwater-induced soil erosion occurring in the forest is a special phenomenon of soil erosion in many red soil areas. Detection of such soil erosion is essential for developing land management to reduce soil loss in areas including southern China and other red soil regions of the world. Remotely sensed canopy cover is often used to determine the potential of soil erosion over a large spatial scale, which, however, becomes less useful in forest areas. This study proposes a new remote sensing method to detect soil erosion under forest canopy and presents a case study in a forest area in southern China. Five factors that are closely related to soil erosion in forest were used as discriminators to develop the model. These factors include fractional vegetation coverage, nitrogen reflectance index, yellow leaf index, bare soil index and slope. They quantitatively represent vegetation density, vegetation health status, soil exposure intensity and terrain steepness that are considered relevant to forest soil erosion. These five factors can all be derived from remote sensing imagery based on related thematic indices or algorithms. The five factors were integrated to create the soil erosion under forest model (SEUFM) through Principal Components Analysis (PCA) or a multiplication method. The case study in the forest area in Changting County of southern China with a Landsat 8 image shows that the first principal component-based SEUFM achieves an overall accuracy close to 90%, while the multiplication-based model reaches 81%. The detected locations of soil erosion in forest provide the target areas to be managed from further soil loss. The proposed method provides a tool to understand more about soil erosion in forested areas where soil erosion is usually not considered an issue. Therefore, the method is useful for soil conservation in forest.

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 Modelling soil erosion at European scale: towards harmonization and reproducibility

2014 ◽  
Vol 2 (4) ◽  
pp. 2639-2680 ◽  
Author(s):  
C. Bosco ◽  
D. de Rigo ◽  
O. Dewitte ◽  
J. Poesen ◽  
P. Panagos
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Computational Modelling ◽  
Mitigation Strategies ◽  
Rainfall Erosivity ◽  
Large Spatial Scale ◽  
Nutrient Contents ◽  
Continental Scale ◽  
Country Level ◽  
Soil Erosion By Water

Abstract. Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale. A new approach for modelling soil erosion at large spatial scale is here proposed. It is based on the joint use of low data demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available datasets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country level statistics of pre-existing European maps of soil erosion by water is also provided.

scholarly journals Assessment and Prevention Strategies of Soil Surface Crusting Caused by Rainfall Events: Case Study of Sebeya Catchment Agricultural Land in Rwanda

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Félicien Majoro ◽  
Umaru Garba Wali ◽  
Omar Munyaneza ◽  
François-Xavier Naramabuye ◽  
Concilie Mukamwambali
Keyword(s):  
Soil Erosion ◽  
Cover Crops ◽  
Soil Conservation ◽  
Soil Loss ◽  
Field Experiments ◽  
Agricultural Land ◽  
Soil Surface ◽  
Water Infiltration ◽  
Vegetative Cover ◽  
Field Plots

The history of soil erosion is an integral part of the agriculture. All over the world, wherever human being started the agricultural operations, there exists the problem of soil erosion in some extent. Soil erosion leads to the reduction of water infiltration rate and enhances runoff and soil degradation. This study focuses on Sebeya catchment located in the Western part of Rwanda. The main objective of this study was to assess various preventive measures against soil surface crusting and development of runoff coefficients in order to minimize the soil loss in Sebeya catchment agricultural fields. The proposed methodology was much concerned with the efficiency analysis of soil conservation practice of mulching in maize cover crops. The names of the three experimental field plots sited are Maize-Fertilizer-Mulching (MFM), Maize-Fertilizer (MF) and Bare Soil (BS) which were set in Rugerero Sector of Rubavu District. Each of these 3 plots was constructed with its runoff collecting tank and they were under similar conditions except land cover. Samples of soil from field plots and water from runoff collecting tanks were tested for soil classification and soil loss estimation from each plot respectively. The analysis of results showed that soil of the experimental plots is a gravelly sand with (sand:56.27%; clay and silt: 3.24% and gravel: 40.49%). Also, the results showed that the plot coded as MFM, has high moisture content with low runoff and soil loss compared to 2 other plots. This research revealed that soil conservation practices such as surface mulching and vegetative cover reduce runoff, soil loss and are well recommended for preventing and controlling soil surface crusting. Keywords: Soil erosion, mulching, soil crusting, field experiments, Rwanda

scholarly journals How Important Is the Number of Points and Plot Size for Estimating Soil Erosion in Vineyards?

Proceedings ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 29
Author(s):  
Barrena-González ◽  
Rodrigo-Comino ◽  
Pulido ◽  
Cerdà
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Standard Procedure ◽  
Soil Surface ◽  
Huge Amount ◽  
Graft Union ◽  
Sw Spain ◽  
Plot Size ◽  
Study Case ◽  
First Time

Some issues remain still unclear in the studies related to soil erosion in vineyards: (i) the accuracy of the measures; (ii) the standardization of the procedures; and, (iii) the huge amount of viticultural areas that are not still measured. In this investigation, we will show research in a non-studied viticultural region using a standard procedure before tested in other vineyards (ISUM -Improved Stock Unearthing Method-), testing different plot sizes and a number of measures. We will estimate soil loss rates in the Tierra de Barros (Extremadura, SW Spain) using the graft union of the vines as a passive biomarker of the soil surface level changes and extra-measures in the inter-row areas. For this study case, for the first time, ISUM was applied to three inter-row and four rows in order to confirm how many points and transects must be measured.

scholarly journals Soil Erosion and Gaseous Emissions

2020 ◽  
Vol 10 (8) ◽  
pp. 2784 ◽  
Author(s):  
Rattan Lal
Keyword(s):  
Soil Erosion ◽  
Net Primary Productivity ◽  
Soil Surface ◽  
Enrichment Ratio ◽  
Strong Impact ◽  
Gaseous Emissions ◽  
Research Information ◽  
Use Efficiency ◽  
Ch4 And N2o ◽  
Soil Erosion By Water

Accelerated soil erosion by water and wind involves preferential removal of the light soil organic carbon (SOC) fraction along with the finer clay and silt particles. Thus, the SOC enrichment ratio in sediments, compared with that of the soil surface, may range from 1 to 12 for water and 1 to 41 for wind-blown dust. The latter may contain a high SOC concentration of 15% to 20% by weight. The global magnitude of SOC erosion may be 1.3 Pg C/yr. by water and 1.0 Pg C/yr. by wind erosion. However, risks of SOC erosion have been exacerbated by the expansion and intensification of agroecosystems. Such a large magnitude of annual SOC erosion by water and wind has severe adverse impacts on soil quality and functionality, and emission of multiple greenhouse gases (GHGs) such as CO2, CH4, and N2O into the atmosphere. SOC erosion by water and wind also has a strong impact on the global C budget (GCB). Despite the large and growing magnitude of global SOC erosion, its fate is neither adequately known nor properly understood. Only a few studies conducted have quantified the partitioning of SOC erosion by water into three components: (1) redistribution over land, (2) deposition in channels, and (3) transportation/burial under the ocean. Of the total SOC erosion by water, 40%–50% may be redistributed over the land, 20%–30% deposited in channels, and 5%–15% carried into the oceans. Even fewer studies have monitored or modeled emissions of multiple GHGs from these three locations. The cumulative gaseous emissions may decrease at the eroding site because of the depletion of its SOC stock but increase at the depositional site because of enrichment of SOC amount and the labile fraction. The SOC erosion by water and wind exacerbates climate change, decreases net primary productivity (NPP) and use efficiency of inputs, and reduces soils C sink capacity to mitigate global warming. Yet research information on global emissions of CH4 and N2O at different landscape positions is not available. Further, the GCB is incomplete and uncertain because SOC erosion is not accounted for. Multi-disciplinary and watershed-scale research is needed globally to measure and model the magnitude of SOC erosion by water and wind, multiple gaseous emissions at different landscape positions, and the attendant changes in NPP.

scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection: A Case of Fincha Catchment, Ethiopia

2021 ◽  
Vol 14 ◽  
pp. 117862212110462
Author(s):  
Meseret Wagari ◽  
Habtamu Tamiru
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Physical Factors ◽  
Rainfall Erosivity ◽  
Rusle Model ◽  
Raster Calculator ◽  
Gis Environment ◽  
Elevation Model ◽  
The Individual ◽  
P Factor

In this study, Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) platforms were successfully applied to quantify the annual soil loss for the protection of soil erosion in Fincha catchment, Ethiopia. The key physical factors such as rainfall erosivity ( R-factor), soil erodibility ( K-factor), topographic condition (LS-factor), cover management ( C-factor), and support practice ( P-factor) were prepared in GIS environment from rainfall, soil, Digital Elevation Model (DEM), Land use/Land cover (LULC) respectively. The RUSLE equation was used in raster calculator of ArcGIS spatial tool analyst. The individual map of the derived factors was multiplied in the raster calculator and an average annual soil loss ranges from 0.0 to 76.5 t ha−1 yr−1 was estimated. The estimated annual soil loss was categorized based on the qualitative and quantitative classifications as Very Low (0–15 t ha−1 yr−1), Low (15–45 t ha−1 yr−1), Moderate (45–75 t ha−1 yr−1), and High (>75 t ha−1 yr−1). It was found from the generated soil erosion severity map that about 45% of the catchment area was vulnerable to the erosion with an annual soil loss of (>75 t ha−1 yr−1), and this demonstrates that the erosion reduction actions are immediately required to ensure the sustainable soil resources in the study area. The soil erosion severity map generated based on RUSLE model and GIS platforms have a paramount role to alert all stakeholders in controlling the effects of the erosion. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss protection practices.

scholarly journals Study of Soil Erosian at a Site near Chemical Engineering Laboratory in UNIMAS

2013 ◽  
Vol 4 (2) ◽  
pp. 1-6
Author(s):  
Fizzahutiah Taha ◽  
Shenbaga R. Kaniraj
Keyword(s):  
Soil Erosion ◽  
Urban Areas ◽  
Soil Loss ◽  
Chemical Engineering ◽  
Environmental Concern ◽  
Control Measure ◽  
Soil Surface ◽  
Bare Soil ◽  
Erosion Risk ◽  
A Site

Soil erosion is one of the problems of environmental concern. Natural causes such as rainfall and human development activities are the two main factors that can cause soil erosion. In order to control soil erosion, especially in urban areas, the bare soil surface needs to be covered by plants as much as possible. Re-vegetation, the best permanent erosion control measure, might take time to be complete. Therefore, some suitable temporary measures should be applied to minimize the amount of soil loss. Topographical features and climate are among the factors that determine the amount of soil erosion. In order to control the rate of erosion, it is important to estimate the amount of soil loss. Universal Soil Loss Equation (USLE) is one of the approaches to estimate the rate of soil loss. In this study, the topographical features of a site prone to erosion within University Malaysia Sarawak (UNIMAS), were investigated by field survey. Laboratory experiments were carried out on soil samples collected from the site. Theparameters for use in USLE were evaluated. The soil loss at the site in 2011 was estimated as 52.85 t ha-1 and the soil erosion risk atthe site was categorized as moderately high. 

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