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

Soil Research ◽  
2018 ◽  
Vol 56 (4) ◽  
pp. 356 ◽  
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.

scholarly journals 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)

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.

scholarly journals Geospatial Assessment of Soil Erosion Intensity and Sediment Yield Using the Revised Universal Soil Loss Equation (RUSLE) Model

2020 ◽  
Vol 9 (6) ◽  
pp. 356 ◽  
Author(s):  
Ahsen Maqsoom ◽  
Bilal Aslam ◽  
Usman Hassan ◽  
Zaheer Abbas Kazmi ◽  
Mahmoud Sodangi ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Sediment Yield ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Rusle Model ◽  
High Severity ◽  
Quantitative Mapping ◽  
Severity Class ◽  
Very High ◽  
Soil Loss Equation

Land degradation caused by soil erosion is considered among the most severe problems of the 21stcentury. It poses serious threats to soil fertility, food availability, human health, and the world ecosystem. The purpose of the study is to make a quantitative mapping of soil loss in the Chitral district, Pakistan. For the estimation of soil loss in the study area, the Revised Universal Soil Loss Equation (RUSLE) model was used in combination with Remote Sensing (RS) and Geographic Information System (GIS). Topographical features of the study area show that the area is more vulnerable to soil loss, having the highest average annual soil loss of 78 ton/ha/year. Maps generated in the study show that the area has the highest sediment yield of 258 tons/ha/year and higher average annual soil loss of 450 tons/ha/year. The very high severity class represents 8%, 16% under high, 21% under moderate, 12% under low, and 13% under very low soil loss in the Chitral district. The above study is helpful to researchers and planners for better planning to control the loss of soil in the high severity zones. Plantation of trees and structures should be built like check dams, which effectively control the soil erosion process.

scholarly journals Soil erosion and sediment yield assessment using RUSLE and GIS-based approach in Anjeb watershed, Northwest Ethiopia

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Lewoye Tsegaye ◽  
Rishikesh Bharti
Keyword(s):  
Soil Erosion ◽  
Land Use Planning ◽  
Sediment Yield ◽  
Soil Loss ◽  
Loss Rate ◽  
Sediment Accumulation ◽  
Delivery Ratio ◽  
Sediment Delivery ◽  
Very High ◽  
Soil Loss Rate

AbstractSoil erosion is a serious and continuous environmental problem in Ethiopia. Lack of land use planning, environmental protection, over-cultivation, and overgrazing are prominent causes of erosion and sedimentation. This study is conducted in Anjeb watershed located in the Upper Blue Nile Basin, Ethiopia. In this study, the quantity and distribution of soil erosion, sediment delivery ratio (SDR), and sediment yield of the watershed were assessed by employing remote sensing, geographic information system (GIS), and revised universal soil loss equation analysis capabilities. Important data sets of topography, soil, conservations practices, cover management, and rainfall factors were processed and superimposed in GIS analysis, and soil loss rate, SDR, and sediment yield of the watershed were derived. Based on the result found, the watershed was categorized into six classes of erosion: slight (0–5), moderate (5–10), high (10–15), very high (15–30), severe (30–50), and very severe (> 50) t ha−1 yr−1. The estimated average annual soil loss was 17.3 t ha−1 yr−1. The soil loss rate is higher in the steeper and topographically dissected part of the watershed. The average sediment delivery capacity was about 0.122. The result showed that the average sediment yield in the watershed was grouped into classes of low (< 2.5), moderate (2.5–7.5), high (7.5–12.5), very high (12.5–22.5), severe (22.5–40), and very severe (> 40) t ha−1 yr−1. It is found that from a total of 20,125.5 t yr−1 eroded soil over the whole watershed 2254.5 t yr−1 of sediment has been brought and deposited to the channels. Sediment accumulation from the watershed threatens the storage capacity and life span of Anjeb reservoir which is the source of irrigation water downstream. The study provides an insight to planners and resource managers to design and implement practices of watershed management to reduce erosion and enhance land productivity and to minimize the reservoir sediment accumulation.

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

2019 ◽  
Vol 8 (6) ◽  
pp. 456-462 ◽  
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.

scholarly journals 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.

scholarly journals A GIS-based estimation of soil erosion parameters for soil loss potential and erosion hazard in the city of Kinshasa, the Democratic Republic of Congo

2018 ◽  
Vol 378 ◽  
pp. 51-57 ◽  
Author(s):  
Martin Tshikeba Kabantu ◽  
Raphael Muamba Tshimanga ◽  
Jean Marie Onema Kileshye ◽  
Webster Gumindoga ◽  
Jules Tshimpampa Beya
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Geographical Information ◽  
Republic Of Congo ◽  
Erosion Hazard ◽  
The City ◽  
Very High

Abstract. Soil erosion has detrimental impacts on socio economic life, thus increasing poverty. This situation is aggravated by poor planning and lack of infrastructure especially in developing countries. In these countries, efforts to planning are challenged by lack of data. Alternative approaches that use remote sensing and geographical information systems are therefore needed to provide decision makers with the so much needed information for planning purposes. This helps to curb the detrimental impacts of soil erosion, mostly emanating from varied land use conditions. This study was carried out in the city of Kinshasa, the Democratic Republic of Congo with the aim of using alternative sources of data, based on earth observation resources, to determine the spatial distribution of soil loss and erosion hazard in the city of Kinshasa. A combined approach based on remote sensing skills and rational equation of soil erosion estimation was used. Soil erosion factors, including rainfall-runoff erosivity R), soil erodibility (K), slope steepness and length (SL), crop/vegetation and management (C) were calculated for the city of Kinshasa. Results show that soil loss in Kinshasa ranges from 0 to 20 t ha−1 yr−1. Most of the south part of the urban area were prone to erosion. From the total area of Kinshasa (996 500 ha), 25 013 ha (2.3 %) is of very high ( >  15 t ha−1 yr−1) risk of soil erosion. Urban areas consist of 4.3 % of the area with very high ( >  15 t ha−1 yr−1) risk of soil erosion compared to a very high risk of 2.3 % ( >  15 t ha−1 yr−1) in the rural area. The study shows that the soil loss in the study area is mostly driven by slope, elevation, and informal settlements.

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

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.

scholarly journals Soil erosion by snow gliding – a first quantification attempt in a subalpine area in Switzerland

2014 ◽  
Vol 18 (9) ◽  
pp. 3763-3775 ◽  
Author(s):  
K. Meusburger ◽  
G. Leitinger ◽  
L. Mabit ◽  
M. H. Mueller ◽  
A. Walter ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Sediment Yield ◽  
Soil Loss ◽  
Water Erosion ◽  
Erosion Rates ◽  
The Difference ◽  
Snow Gliding

Abstract. Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide 137Cs and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the 137Cs method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959–2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha−1 yr−1 in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha−1 yr−1 was found. The difference in long-term erosion rates determined with RUSLE and 137Cs confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2 = 0.64; p < 0.005) and to the snow deposition sediment yields (R2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions.

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