Assessment of Soil Erosion in the Watershed of Upper Lake, Bhopal using Remote Sensing and GIS

Recognizable proof of soil erosion territories and to propose or apply preventive measures is significant advance in the management of watershed. For structuring a watershed and to conserve it appropriately assessment of soil erosion plays a significant role. With the headway of innovation and advancement of GIS and Remote Sensing researchers and scientists can assess soil erosion using various developed model. In this study, Universal Soil Loss Equation (USLE) has been utilized to gauge soil disintegration inside the Upper Lake Bhopal, India. Catchment territory of Upper Lake, Bhopal has been partitioned into 24 sub zones and every one of them were organized according to the erosion occurring. The normal yearly soil misfortune guide has been acquired by coordinating R, K, LS, C and P factor maps and it fluctuates from 0.00 to 2735.45 t/ha/yr over the watershed. All the 24 sub watershed have been named as Krishna's sub watershed (KW). The average soil loss from sub-watersheds have been figured and changes between 1.26 (KW-21) t/ha/yr to 99.04 (KW-3) t/ha/yr. The total soil loss in the watershed is determined as 19.6 t/ha/yr All sub-watersheds have been arranged into five classes specifically extremely high, high, moderate, low and low classifications based on final priority. Watersheds going under exceptionally high need covers 30.51% zone of study region, high need covers 22.31% zone, moderate need covers 25.46% zone of study territory, low need covers 14.45% region of study region, goes under extremely low need which spreads 7.26% zone of study region.

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Potential Soil Loss Estimation and Erosion-Prone Area Prioritization Using RUSLE, GIS, and Remote Sensing in Chereti Watershed, Northeastern Ethiopia

Air Soil and Water Research ◽

10.1177/1178622120985814 ◽

2021 ◽

Vol 14 ◽

pp. 117862212098581

Author(s):

Ajanaw Negese ◽

Endalkachew Fekadu ◽

Haile Getnet

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Conservation Planning ◽

Water Conservation ◽

Soil Loss ◽

Rainfall Erosivity ◽

Gis And Remote Sensing ◽

Soil Erosion Rate ◽

Conservation Measures ◽

Prone Area

Soil erosion by water is the major form of land degradation in Chereti watershed, Northeastern Ethiopia. This problem is exacerbated by high rainfall after a long period of dry seasons, undulating topography, intensive cultivation, and lack of proper soil and water conservation measures. Hence, this study aimed to estimate the 23 years (1995-2018) average soil erosion rate of the watershed and to identify and prioritize erosion-vulnerable subwatersheds for conservation planning. The integration of the revised universal soil loss equation (RUSLE), geographic information system, and remote sensing was applied to estimate the long-term soil loss of the watershed. The RUSLE factors such as rainfall erosivity ( R), soil erodibility ( K), topography ( LS), cover and management ( C), and support and conservation practices ( P) factors were computed and overlayed to estimate the soil loss. The result showed that the annual soil loss rate of the watershed ranged up to 187.47 t ha−1 year−1 in steep slope areas with a mean annual soil loss of 38.7 t ha−1 year−1, and the entire watershed lost a total of about 487 057.7 tons of soil annually. About 57.9% of the annual watershed soil loss was generated from 5 subwatersheds which need prior intervention for the planning and implementation of soil conservation measures. The integrated use of RUSLE with GIS and remote sensing was found to be indispensable, less costly, and effective for the estimation of soil erosion, and prioritization of vulnerable subwatersheds for conservation planning.

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Terrain Characterization and Soil Erosion Risk Assessment for Watershed Prioritization Using Remote Sensing and GIS (A case study of Nawagaon Maskara Rao Watershed, Saharanpur, India)

Forum Geografi ◽

10.23917/forgeo.v23i1.5001 ◽

2009 ◽

Vol 23 (1) ◽

pp. 86

Author(s):

Beny Harjadi

Keyword(s):

Remote Sensing ◽

Risk Assessment ◽

Land Use ◽

Soil Erosion ◽

Soil Conservation ◽

Soil Loss ◽

Remote Sensing And Gis ◽

Erosion Risk ◽

Soil Erosion Risk ◽

Conservation Measures

Soil erosion is crucial problem in India where more than 70% of land in degraded. This study is to establish conservation priorities of the sub watersheds across the entire terrain, and suggest suitable conservation measures. Soil conservation practices are not only from erosion data both qualitative SES (Soil Erosion Status) model and quantitative MMF (Morgan, Morgan and Finney) model erosion, but we have to consider LCC (Land Capability Classification) and LULC (Land Use Land Cover). Study demonstrated the use of RS (Remote Sensing) and GIS (Geographic Information System) in soil erosion risk assessment by deriving soil and vegetation parameters in the erosion models. Sub-watersheds were prioritized based on average soil loss and the area falls under various erosion risk classes for conservation planning. The annual rate of soil loss based on MMF model was classified into five soil erosion risk classes for soil conservation measures. From 11 sub watersheds, for the first priority of the watershed is catchment with the small area and the steep slope. Recommendation for steep areas (classes VI, VII, and VIII) land use allocation should be made to maintain forest functions.

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Soil erosion analysis by RUSLE and sediment yield models using remote sensing and GIS in Kelantan state, Peninsular Malaysia

Soil Research ◽

10.1071/sr17193 ◽

2018 ◽

Vol 56 (4) ◽

pp. 356 ◽

Cited By ~ 4

Author(s):

M. T. Anees ◽

K. Abdullah ◽

M. N. M. Nawawi ◽

N. A. N. Norulaini ◽

M. I. Syakir ◽

...

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Sediment Yield ◽

Soil Loss ◽

High Probability ◽

Peninsular Malaysia ◽

Remote Sensing And Gis ◽

Agricultural Activities ◽

Steep Slopes ◽

Very High

The present study used pixel-based soil erosion analysis through Revised Universal Soil Loss Equation (RUSLE) and a sediment yield model. The main motive of this study is to find soil erosion probability zones and accordingly prioritise watersheds using remote sensing and Geographic Information System (GIS) techniques in Kelantan state, Peninsular Malaysia. The catchment was divided into 82 watersheds and soil loss of the catchment was calculated. Soil loss and sediment yield were divided into five categories ranging from very low to very high. Maximum area of the very high soil-loss category was observed in uncultivated land and the maximum area of very low soil-loss category was in forest. Soil erosion probability zones were also divided into five categories in which 36.1% of the area experienced zero soil erosion and 20.1% and 17.8% represented very high and high probability zones respectively. The maximum very high and high probability zones were 61.6% and 28.5% of the watershed area respectively. Prioritisation was according to the area covered by very high and high soil erosion probability zones, which showed that out of 82 watersheds, two had the very high and high priority categories respectively. The overall results indicate that high rainfall and agricultural activities enhanced the soil erosion rate on steep slopes in the catchment. Pixel-based soil erosion analysis through remote sensing and GIS was a very effective tool in finding accurate causes of soil erosion. Furthermore, it was suggested that agricultural activities and deforestation should be stopped on steep slopes because of their contribution in increasing soil erosion.

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GIS and Remote Sensing solution for Dalat city’s soil erosion mapping

Science and Technology Development Journal ◽

10.32508/stdj.v19i2.700 ◽

2016 ◽

Vol 19 (2) ◽

pp. 46-54

Author(s):

Trung Van Le ◽

Hoang Thi Kim Nguyen ◽

Anh Thi Ngoc Nguyen

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Conservation ◽

Soil Loss ◽

Point Of View ◽

Gis And Remote Sensing ◽

Thematic Layers ◽

Erosion Risk ◽

Attribute Data ◽

Soil Loss Equation

This paper introduces the solution for Dalat city’s soil erosion mapping using the integration of GIS, Remote Sensing and the Universal Soil Loss Equation (USLE). Each of the USLE factors with associated attribute data are dicussed and the soil erosion parameters were selected and encoded in a GIS database to produce thematic layers. The result demonstrates the soil erosion map that indicates the potential annual soil loss located in each area of land. This map is used to confirm the severe level of soil erosion risk need immediate attention from soil conservation point of view.

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Application of RUSLE integrated with GIS and remote sensing techniques to assess soil erosion in Anambra State, South-Eastern Nigeria

Journal of Water and Climate Change ◽

10.2166/wcc.2020.222 ◽

2020 ◽

Vol 11 (S1) ◽

pp. 407-422 ◽

Cited By ~ 1

Author(s):

Fidelis Odedishemi Ajibade ◽

Nathaniel Azubuike Nwogwu ◽

Bashir Adelodun ◽

Taofeeq Sholagberu Abdulkadir ◽

Temitope Fausat Ajibade ◽

...

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Erosivity ◽

Landsat 8 ◽

Gis And Remote Sensing ◽

Anambra State ◽

Remote Sensing Techniques ◽

Soil Loss Equation

Abstract Soil erosion and mass movement processes spread across Anambra State in Nigeria, therefore making management and conservation techniques expensive and difficult in execution across the entire state. This study employed the Revised Universal Soil Loss Equation (RUSLE) model with the integration of geographic information system (GIS) and remote sensing techniques to assess the risk of soil erosion and hotspots in the area. Remotely sensed data such as Landsat 8 imagery, Shuttle Radar Topography Mission (SRTM) imagery, Era-Interim coupled with world soil database were used as digital data sources for land use map, digital elevation model, rainfall and soil data, respectively, to generate the Universal Soil Loss Equation (USLE) parameters. The results indicated vulnerability levels in low, medium and high cover areas of 4,143.62 (91%), 332.29 (7%) and 84.06 (2%) km2, respectively, with a total soil loss between 0 and 181.237 ton/ha/yr (metric ton per hectare per year). This study revealed that high rainfall erosivity, steep and long slopes, and low vegetation cover were the main factors promoting soil loss in the area. Thus, the amount of soil loss in Anambra State is expected to increase with climate change and anthropogenic activities.

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Temporal Variation in Water Induced Soil Erosion by RUSLE Model Using Remote Sensing and GIS

10.29007/271c ◽

2018 ◽

Author(s):

Aditi Bhadra ◽

H. Lalramnghaki ◽

L. G. Kiba ◽

Arnab Bandyopadhyay

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Temporal Variation ◽

Soil Loss ◽

Temporal Variations ◽

Equation Model ◽

Remote Sensing And Gis ◽

Rainfall Erosivity ◽

Erosion Risk ◽

Modis Ndvi

Soil erosion by various agents is one of the major threats of land degradation throughout the world. Revised Universal Soil Loss Equation model integrated with remote sensing and GIS was employed to assess soil erosion in the Mago basin of Arunachal Pradesh, India for a period of ten years (2004–2013). The rainfall erosivity (R-factor) was calculated using ten years rainfall data. ASTER DEM of 30 m resolution was used to generate the LS-factor map. Soil map and soil samples were analyzed to generate soil erodibility (K) map. MODIS NDVI images were used to obtain C-factor maps. The average annual soil loss was estimated and spatial and temporal variations of annual soil erosion were analyzed. The largest portion of the snow or glacier free area was observed under slight erosion and the rest of the area under moderate to very severe erosion risk zones. The temporal variation in the area under slight soil erosion showed a decreasing trend. Increasing trends were observed over the years in areas under moderate to very severe soil erosion classes. The average soil loss by water for each year crossed permissible soil loss limit of 12 t ha-1 year-1 except for the year 2006.

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Applications of remote sensing and GIS for watershed characterization and soil loss assessment of tons watershed in Dehradun, Garhwal Himalaya

International Journal of Agricultural and Applied Sciences ◽

10.52804/ijaas2020.1113 ◽

2020 ◽

Vol 1 (1) ◽

pp. 56-67

Author(s):

P.C. Chanyal ◽

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Watershed Management ◽

Soil Loss ◽

Remote Sensing And Gis ◽

Garhwal Himalaya ◽

Rainfall Erosivity ◽

Loss Assessment ◽

Factor C

Watershed characterization is the most important part of watershed management which includes soil loss, soil loss assessment indicates the amount of soil loss or erosion in ton/hectare/ year through applying to Geospatial techniques as Remote sensing and GIS. The agricultural land is being lost by manmade as well natural whereas manmade or anthropogenic factor accelerates erosion of soil. It is a worldwide phenomenon leading to loss of decrease of water table availability for plants, increases runoff from the more impermeable subsoil, and loss of nutrients from the soil. Watershed management and assessment of soil loss are most helpful for planning and batter management in a watershed and planning units. Remote sensing and GIS along with the satellite image-based model approach provides a scientific, quantitative, and applied result. It can compute a consistent outcome of soil erosion and sediment yield for a wide range of areas under all climatic circumstances. Revised Universal Soil Loss Equation (RUSLE) apply to soil loss, which is integrated with Remote Sensing and GIS in Tons watershed lies between 77°56’05” E to 78°01’01” East longitude and 30° 21’05” N to 30°26’51” North latitude, having 97.02 km2 area (9,702 hectares) under the sub-tropical climatic region of Uttarakhand. The present case study based on computational with software and geospatial technologies results come i.e. A = is the computed soil loss per unit area, R = is the rainfall erosivity, K = is the soil erodibility factor, L = is the slope-length factor, C = is the cover and management factor, P = is the support practice factor. The rainfall erosivity (R=87.5 + 0.375 × R), C P is under range 0.006-0.8, Soil Erosion Risk range is slight to High 51.40% and 0.85% total area of the study region. Average annual soil loss ton/ha/year indicated in different land-use classification as lowest soil loss found in River bed (0.17 ton/ha/year) and highest shown in the open forest (56.58 ton/ha/year) in 2016. The study area comes under a low probability zone and partially comes under a moderate and moderate-high zone. The case study can be highly recommended and will help to implementation of management of soil loss and soil conservation practice in the Tons watershed as well as Himalayan regions. Keywords: RUSLE, Tons Watershed, Soil Loss, Remote Sensing & GIS, Garhwal Himalaya.

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