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INTRODUCTION
Soil erosion occurs when the protective layer of topsoil, rich in organic matter and nutrients, is removed by natural forces like wind and water. Soil erosion, the gradual wearing away of topsoil, is a major environmental challenge with far-reaching consequences. While seemingly slow and gradual, its impact on our environment, food security, and overall well being is significant. This introduction explores the critical need to understand and estimate soil erosion, highlighting the urgency for action and the tools we use to combat this global challenge.
Here's a breakdown of the process:
>Detachment: Rain, wind, or other agents loosen and detach soil particles.
>Transport: Detached particles are carried away by water or wind, often ending up in rivers, lakes,
>Deposition: Eroded soil is deposited in new locations, sometimes forming sediments that can clog waterways or damage infrastructure.
Topsoil is vital for plant growth, providing essential nutrients. Erosion depletes these nutrients, reducing agricultural yields and threatening food security. Eroded soil particles enter waterways, contaminating water sources and harming aquatic ecosystems. This impacts drinking water quality and disrupts the balance of aquatic life. Erosion can lead to the degradation of land, making it unsuitable for agriculture or other uses. This can result in desertification, loss of biodiversity, and increased vulnerability to natural disasters. Soil erosion reduces agricultural productivity, increases water treatment costs, and damages infrastructure, leading to significant economic losses.
Study area:
The Nilgiris, also known as the Blue Mountains, present a compelling study area for soil erosion estimation due to its unique geographical and ecological features, combined with significant human impact. The Nilgiris covers a vast area, making it challenging to provide precise coordinates. The coordinates provided earlier for Ooty (1 1.4041 0 N, 76.6807 0 E) and Coonoor (l I .3201 0 N, 76.7983 0 E) represent two key locations within the region. The Nilgiris provide a unique and crucial study area for understanding and estimating soil erosion. Its complex topography, human impacts, and climate change vulnerabilities make it a critical region for exploring sustainable land management practices and mitigating the consequences of erosion.
The Nilgiris are characterized by steep slopes, particularly in the higher elevations. This topography makes them susceptible to increased runoff and erosion, especially during heavy rainfall. The region experiences a significant elevational gradient, ranging from lower elevations with more agriculture to higher, more forested areas. This creates variations in rainfall, soil types, and land cover, making it ideal for studying how soil erosion changes with altitude.
METHODOLOGY:
The Nilgiris, also known as the Blue Mountains, present a compelling study area for soil erosion estimation due to its unique geographical and ecological features, combined with significant human impact. The Nilgiris covers a vast area, making it challenging to provide precise coordinates. The coordinates provided earlier for Ooty (1 1.4041 0 N, 76.6807 0 E) and Coonoor (l I .3201 0 N, 76.7983 0 E) represent two key locations within the region. The Nilgiris provide a unique and crucial study area for understanding and estimating soil erosion. Its complex topography, human impacts, and climate change vulnerabilities make it a critical region for exploring sustainable land management practices and mitigating the consequences of erosion.
USLE was developed by Wischmeier and Smith in the 1950s.
USLE estimates the long-term average annual rate of erosion on a field slope based on rainfall pattern, soil type, topography, crop system and management practices.
Where,
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A is the average annual soil loss (tons halyearl ), R is the rainfall erosivity (MJmm ha 111 yearl ),
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K is the soil erodibility factor (tons ha R unitl),
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LS is the topographic factor (dimensionless),
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C is the cropping management factors (dimensionless),
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P is the practice support factor (dimensionless)
INPUT PARAMETERS:
I.RAINFALL EROSIVITY(R) FACTOR:
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Rainfall erosivity is the kinetic energy of raindrop's impact and the rate of associated runoff
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The R-factor measures the impact of rainfall on erosion in MJ mm ha—I h—l year—I.
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The rainfall erosion factor is vital for assessing soil erosion. Heavy rainfall increases erosion by causing more runoff and soil detachment.
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Data Source: Global Rainfall Erosivity (https://esdac.jrc.ec.europa.eu/content/global-rainfall-erosivity)
2.S01L ERODIBILITY (K) FACTOR:
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Soil erodibility represents the effect of soil properties and soil profile characteristics on soil loss.
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Soil erodibility is crucial in determining erosion susceptibility. Sandy soils erode easily due to loose particles, while clay soils are more resistant. Organic matter enhances soil stability and reduces erosion
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Data Source: Harmonized World Soil Database v 1.2 (https://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HTML/)
From that metadata we can find the soil textural class and organic carbon and from that we can calculate Organic matter with the help of below table.
Note that the table in the guide accounts for % organic matter (0M), not just organic carbon (OC). If we do not know the conversion value for the area, the value OC is multiplied by 1.72 to get 0M. (The references for conversion factors are given in IPCC-AFOLU report 2006.)
From the organic matter with the help of table the F factor is predicted and change the map symbology based on the K factor.
3.TOPOGRAPHIC (LS) FACTOR:
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Topographic factors LS consist of slope length L and slope steepness S.
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Slope Length: Longer slopes lead to greater water runoff and erosion.
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Slope Steepness: Steeper slopes increase the speed of water flow, which enhances soil detachment and erosion.
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Data source: USGS Earth Explorer.
Slope Steepness
where, ß is slope angle in percentage, n ranges from 1.0-1.3.
Slope Length:
L = [(FA * cell (Moore and Wilson, 1992)
where, FA is flow accumulation, cell size is the size of DEM and m ranges from 0.2-0.6.
Together, these factors determine how effectively water can erode soil as it flows downhill.
4.CROP [VEGETATION AND MANAGEMENT FACTOR(C):
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Used to determine the relative effectiveness of soil and crop management systems in preventing soil loss.
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Value can be assigned for different land cover classes from look-up tables in literature.
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Land Cover Data source: Sentinel-2 Land Use/Land Cover. (https://esri.maps.arcgis.com/apps/instant/media/index.html?appid=fc92d38533d440078f17678ebc20e8e2)
The C factor, or Cover Management factor, affects soil erosion by representing the impact of land cover and vegetation:
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Vegetation Cover: More vegetation reduces erosion by protecting the soil and slowing water runoff.
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Land Use: Different types of land use, such as agricultural practices or urban development, influence how much erosion occurs.
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Essentially, the C factor measures how well the surface cover prevents soil erosion.
Several references on estimating these factors can be found online:
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USLE Fact Sheet
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U.N. Food and Agriculture Organization
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RUSLE handbook (Renard et al., 1997)
The topographic class name is assigned with the help of C factor from the table and add the field called topographic class in the attribute table and change the map symbology according to the topographic class name.
5.SUPPORT PRACTICE FACTOR(P):
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It reflects the effects of practices that will reduce the amount and rate of the water runoff and thus reduce the amount of erosion.
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Values are obtained from literature based on the farmers' practices.
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For easy interpretation, we can use 1 irrespective of land cover classes
The P factor, or Support Practice factor, affects soil erosion by representing the impact of practices that reduce runoff and soil erosion. These practices include:
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Contour Plowing: Plowing along the contours of a slope to reduce runoff and erosion.
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Terracing: Creating terraces on slopes to slow water flow and capture runoff.
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Strip Cropping: Alternating strips of different crops to reduce soil erosion.
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Cover Crops: Planting cover crops to protect the soil and reduce erosion.
RESULT AND CONCLUSION:
The final soil erosion map, generated using the Universal Soil Loss Equation (USLE) with comprehensive raster calculations of all relevant factors, provides a detailed visualization of soil erosion risk across the study area.
By combining these factors, the final map delineates areas of varying erosion risk, from low to high. This spatial representation allows for targeted erosion control measures, helps prioritize areas requiring intervention, and guides land management decisions.
High erosion risk zones, indicated in lighter shades, should be the focus of immediate conservation efforts, while moderate and low-risk areas can benefit from routine monitoring and maintenance
The overall analysis reveals that soil erosion in the Nilgiris is a multifaceted issue driven by natural and anthropogenic factors. The detailed erosion map generated through USLE provides a vital tool for identifying high-risk areas and informing targeted soil conservation strategies. By addressing the identified risk factors and implementing recommended interventions, it is possible to significantly reduce soil erosion, thereby protecting the region's agricultural productivity and environmental health.
Reference
I .Estimation of Soil loss by USLE Model using GIS and Remote Sensing techniques: A case study of Muhuri River Basin, Tripura, India
2.Estimation of Soil loss Using USLE Model for Kuhlman Watershed, Chattisgarh- A Case Study
3.Soil erosion modelled with USLE, GIS, and remote sensing: a case study of Ikkour watershed in Middle Atlas (Morocco)
4.Karydas, C. , et al. (2015). "Evaluation of soil erosion and sediment yield in urban catchments using GIS-based USLE." Journal ofEnvironmental Management, 154, 97-104.
5.Sena, M. , et al. (2017). "Temporal analysis of soil erosion using GIS and remote sensing: A case study of the Lobo watershed." Remote Sensing, 9(7), 678.