Estimating Potential Annual Soil Loss of Watershed in Nigeria Using Rulse in a GIS and Remote Sensing Environment

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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Estimation of soil loss in Seremban, Malaysia using GIS and remote sensing technique

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/169/1/012062 ◽

2018 ◽

Vol 169 ◽

pp. 012062

Author(s):

Goma B Ahmed ◽

A R M Shariff ◽

S K Balasundram ◽

A F B Abdullah

Keyword(s):

Remote Sensing ◽

Soil Loss ◽

Gis And Remote Sensing ◽

Remote Sensing Technique

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Soil loss estimation using RUSLE model, GIS and remote sensing techniques: A case study from the Dembecha Watershed, Northwestern Ethiopia

Geoderma Regional ◽

10.1016/j.geodrs.2017.06.003 ◽

2017 ◽

Vol 11 ◽

pp. 28-36 ◽

Cited By ~ 21

Author(s):

Yaser Ostovari ◽

Shoja Ghorbani-Dashtaki ◽

Hossein-Ali Bahrami ◽

Mehdi Naderi ◽

Jose Alexandre Melo Dematte

Keyword(s):

Remote Sensing ◽

Soil Loss ◽

Loss Estimation ◽

Gis And Remote Sensing ◽

Rusle Model ◽

Remote Sensing Techniques

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

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.e7858.088619 ◽

2019 ◽

Vol 8 (6) ◽

pp. 456-462 ◽

Cited By ~ 1

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Loss ◽

Preventive Measures ◽

Remote Sensing And Gis ◽

Significant Advance ◽

Study Region ◽

Gis And Remote Sensing ◽

P Factor ◽

Factor Maps

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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