scholarly journals Determination of Cover Management and Soil Loss Risk Mapping by Sub-Districts and River Catchments of Cameron Highlands Malaysia

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1181
Author(s):  
Roslan Zainal Abidin ◽  
Mohd Amirul Mahamud ◽  
Mohd Fazly Yusof ◽  
Nor Azazi Zakaria ◽  
Mohd Aminur Rashid Mohd Amiruddin Arumugam
Keyword(s):  
Soil Erosion ◽  
Urban Development ◽  
Land Surface ◽  
Soil Loss ◽  
Department Of Agriculture ◽  
Cameron Highlands ◽  
Data Source ◽  
P Factor ◽  
River Catchments

Uncontrolled deforestation and land clearing for agricultural, urban development, and infrastructure construction without considering cover management (C&P) factors have resulted in severe soil erosion over the land surface of Cameron Highlands in the state of Pahang, Malaysia. Thus, this study determines the C&P factors for the Universal Soil Loss Equation (USLE) to forecast soil loss risk. Land use and land cover recorded by PLANMalaysia and the Department of Agriculture (DOA) Malaysia have produced different C&P factors in Cameron Highlands. The C&P factor produced from PLANMalaysia and the DOA has values ranging between 0.01 to 1.00 and 0.30 to 0.49, respectively. Since the C&P factor varies according to the data source, this study combined both data sources to capture both agricultural and urban development impacts, resulting in an acceptable C&P factor. These new C&P factors have improved the prediction of soil loss risk with 15.63% (10,581.86 hectares) of the Cameron Highlands area classified as having a moderate–critical soil loss risk compared to DOA 7.16% (4844.97 hectares) and PLANMalaysia’s 11.46% (7725.26 hectares). Thus, local authorities must strengthen all regulations and policies to address the predicted moderate–critical soil loss risk in Cameron Highlands, thereby preventing severe soil erosion.

scholarly journals Determination of Cover and Land Management Factors for Soil Loss Prediction in Cameron Highlands, Malaysia

Agriculture ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 16
Author(s):  
Mohd Amirul Mahamud ◽  
Noor Aida Saad ◽  
Roslan Zainal Abidin ◽  
Mohd Fazly Yusof ◽  
Nor Azazi Zakaria ◽  
...  
Keyword(s):  
Land Management ◽  
Land Surface ◽  
Soil Loss ◽  
Study Data ◽  
Data Sets ◽  
Percentage Difference ◽  
Loss Prediction ◽  
Cameron Highlands ◽  
To Come ◽  
P Factor

Many new agricultural activities resulted in severe soil erosion across the Cameron Highlands’ land surface. Therefore, this study determines the cover (C) and land management (P) factors of the USLE for predicting soil loss risk in Cameron Highlands using a Geographic Information System (GIS). For this study, data from the Department of Agriculture Malaysia (DOAM) and the Department of Town and Country Planning Malaysia (PLANMalaysia) were used to generate several C&P factors in the Cameron Highlands. Data from both agencies have resulted in C factors with 0.01 to 1.00 and P factors with 0.30 to 0.49. Due to the cover and land management factor varies depending on the data collected by the various agencies, this study used the two data sets to come up with a C&P factor that accurately reflected both agricultural and urban growth effects. RKLS factors of USLE were obtained from the DOAM with values R (2375–2875), K (0.005), LS (2.5–25), respectively. The Cameron Highlands’ soil loss risk with these new C&P values resulted in a soil loss of 6.72 per cent (4547.22 hectares) from high to critical, with a percentage difference range of −0.77 to +3.37 under both agencies, respectively.

scholarly journals Geospatial Analysis of Soil Erosion Susceptibility and Causative Factors in Anambra State, South East, Nigeria

2021 ◽  
pp. 5-32
Author(s):  
Romanus Udegbunam Ayadiuno ◽  
Dominic Chukwuka Ndulue ◽  
Chinemelu Cosmas Ndichie ◽  
Arinze Tagbo Mozie ◽  
Philip O. Phil-Eze ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Soil Loss ◽  
Vegetation Index ◽  
Anthropogenic Activities ◽  
Rainfall Erosivity ◽  
Anambra State ◽  
Causative Factors

Land degradation is a function of soil erosion leading to soil loss and reduction in crop productivity as well as other socio-economic activities. The menace of soil erosion is challenging due to diverse factors including advertent and inadvertent anthropogenic activities. This study looks at soil erosion susceptibility and causative factors in Anambra State, both static and dynamic with the intent of identifying them, investigating spatial variability of soil loss, relate erodibility to soil properties and causative factors to soil erosion. Eight (8) prominent causative factors (CFs), were identified. These causative factors (CFs) were analyzed using ArcGIS 10.2. Sixty (60) soil samples were extracted randomly, analyzed, and tested. The study identified CFs such as Drainage Density, Erosion Density, Lineament Density, Slope Length, Land Surface Temperature, and Rainfall Erosivity, which contribute to Soil Erodibility (K - Factor). Land Surface Temperature, Soil Moisture Index, Rainfall Erosivity, and Normalized Difference Vegetation Index contributed to the loss of 8.97 ton/ha/yr, 9.1288 ton/ha/yr, 1,1134.7 ton/ha/yr, and 0.245 ton/ha/yr respectively to erosion in Anambra State. Conclusively, the dynamic causative factors influence soil susceptibility and trigger erosion in the State.

scholarly journals GEOSPATIAL TECHNOLOGY BASED SOIL LOSS ESTIMATION FOR SUSTAINABLE URBAN DEVELOPMENT OF BUTWAL SUBMETROPOLITAN CITY, NEPAL

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 137-144
Author(s):  
U. K. Mandal ◽  
K. Kumari
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Urban Development ◽  
Soil Loss ◽  
Urban Land Use ◽  
Sustainable Urban Development ◽  
Lower Percentage ◽  
Significant Difference ◽  
The City ◽  
Soil Unit

Abstract. Geo-spatial technology was attempted to estimate the potential and actual soil loss and its correlative interpretation with physiographic soil units and land use and cover types in Butwal sub-metropolitan city, Central Region of Nepal. Among several empirical and physically based soil erosion models, widely used RKLS and RKLSCP, Revised Universal Soil Loss Equation (RUSLE) were employed to estimate the potential and actual soil loss in the present investigation, respectively. Five years of rainfall, topographic contour-spot height and soil map were basically used as source of information for in-depth investigation. Butwal sub-metropolitan located at foothill of Chure/Siwalik range was found highly sensitive or prone to soil erosion. A total of 32.68 and 1.83 million tons soil was potentially and actually estimated annually being lost from the city. Erosion rates were found highly correlated with the slope of physiographic soil unit. 60.93% of the total potential soil loss was mainly contributed only by physiographic-soil unit 12 with the spatial extent of 34.10% of the city area. This unit was characterized by steeply to very steeply sloping mountainous terrain having dominant slope greater than 30° and loamy skeletal as dominant soil texture. Significant difference was found in the estimation of RKLS and RKLSCP indicating the substantial reduction contribution of soil loss by land use/cover types predominated by forest. after agriculture. Thus physiographic-soil unit 12 having soil loss highest must be given higher priorities for soil conservation and optimum urban land use planning required for sustainable urban development. Lower percentage of actual soil to the potential loss indicated the fact of contribution of cover management and erosional control practice factor in reducing soil erosion in existing situation.

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 Estimation of Soil Erosion Using RUSLE Model and GIS: The Case of Satinskyi Catchment, Western Rwanda

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
R. V Byizigiro ◽  
G Rwanyiziri ◽  
M. Mugabowindekwe ◽  
C. Kagoyire ◽  
M. Biryabarema
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Surface ◽  
Soil Loss ◽  
Slope Angle ◽  
Rainfall Erosivity ◽  
Land Use Patterns ◽  
Rusle Model ◽  
Factor C ◽  
Loss Rates

The problem of soil erosion in Rwanda has been highlighted in previous studies. They have shown that half of the country’s farmland suffers moderate to severe erosion, with the highest soil loss rates found in the steeper and highly rainy northern and western highlands of the country. The purpose of this study was to estimate soil loss in Satinskyi, one of the catchments located in Ngororero District of Western Rwanda. This has been achieved using the Revised Universal Soil Loss Equation (RUSLE) model, which has been implemented in a Geographic Information Systems (GIS) environment. The methods consisted of preparing a set of input factor layers including Slope Length and Steepness (LS) factor, Rainfall Erosivity (R) factor, Soil Erodibility (K) factor, Support Practice (P) factor, and Land Surface Cover Management Factor (C) factor, for the model. The input factors have been integrated for soil loss estimates computation using RUSLE model, and this has enabled to quantitatively assess variations in the mean of the total estimated soil loss per annum in relation to topography and land-use patterns of the studied catchment. The findings showed that the average soil loss in Satinskyi catchment is estimated at 38.4 t/ha/year. It was however found that about 91% of the study area consists of areas with slope angle exceeding 15°, a situation which exposes the land to severe soil loss rates ranging between 31 t/ha/year and 41 t/ha/year. Apart from the steep slope, changes in land use also contribute to high rates of soil loss in the catchment. Keywords: Soil Erosion Estimation, GIS, RUSLE, Satinskyi Catchment, Rwanda

scholarly journals Susceptibility to Soil Erosion and Risk Assessment at Hilly Farms Using Geospatial Techniques

2020 ◽  
Vol 2 ◽  
pp. 6-13
Author(s):  
Nasidi N.M. ◽  
Wayayok A. ◽  
Abdullah A. F. ◽  
Kassim M. S. M.
Keyword(s):  
Risk Assessment ◽  
Soil Erosion ◽  
Best Management Practices ◽  
Soil Loss ◽  
Management Practices ◽  
Traditional Approach ◽  
Erosion Risk ◽  
Risk Levels ◽  
Distance Weighted ◽  
Cameron Highlands

Soil erosion is a serious environmental challenge which persistently diminishes available land resources globally.The impact of soil erosion is more severeat hilly regions where various techniques are deployed to evaluateits risk levels. However, the traditional approach of estimating the magnitude of erosion is tedious, costly, and considerably time consuming. This study was intended to assess the risk associated with soil erosion at hilly areas of Cameron Highlands through geospatial means. The Digital Elevation Model (DEM) with 5m resolution from Interferometric Synthetic Aperture Radar (IfSAR) was utilized to generate the slope inthe highlands. Soil erosion rates was estimated using Universal Soil Loss Equation (USLE), while information about land use and cover were sourced from relevant government agencies. Inversed Distance Weighted (IDW) method of spatial interpolation was applied to predict the values of unknown pixels. The analysis shows that, there is 217.5 km2of the highlands which is greater than 45-degreeaccounted for about 30.5% of the total land area. Moreover, erosion risk assessment indicated that 66.3%, 11.4%, 11.7% and 10.8% are respectively classified as very low, law, moderate and high susceptible to soil erosion. In general, the risk of soil erosion is relatively low and could be attributed to den sevegetation coverage within the study watershed despite the steep slopes where it was found to be at very high risk to soil erosion susceptibility. However, there is need to deploy best management practices to reduce the effect of soil disturbances at hilly areas and prevent excessive soil loss in future.

scholarly journals SOIL EROSION PREDICTION AT THE BASIN SCALE USING THE REVISED UNIVERSAL SOIL LOSS EQUATION (RUSLE) IN A SONGBE’S BASIN

2011 ◽  
Vol 14 (4) ◽  
pp. 86-96
Author(s):  
Tu Tuan Tran
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Measurement Data ◽  
Rain Gauge ◽  
Universal Soil Loss Equation ◽  
Agricultural Ecosystem ◽  
Erosion Prediction ◽  
Basin Scale ◽  
P Factor ◽  
Soil Loss Equation

Soil water erosion is a serious environmental problem affecting large areas of the agricultural ecosystem in Nambo Eastern. Soil erosion not only affects soil quality, in terms of agricultural productivity, but also reduces the availability of water in reservoirs. This study was conducted in the Song Be watershed in Nambo Eastern, to predict potential annual soil loss using the revised universal soil loss equation (RUSLE). The RUSLE factors were calculated for the Song Be watershed: using survey data and rain gauge measurement data. TheRfactor was calculated from annual precipitation data. The K-factor was calculated from soil map scale 1/100000. The LS topographic factor was calculated from a 90 m digital elevation model. The C-factor was calculated from Landsat image. P-factor in absence of detailed data, were set to 1.

Global analysis of support practices in USLE-based soil erosion modeling

2019 ◽  
Vol 43 (3) ◽  
pp. 391-409
Author(s):  
Muqi Xiong ◽  
Ranhao Sun ◽  
Liding Chen
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Field Experiments ◽  
Global Analysis ◽  
Global Scale ◽  
Erosion Modeling ◽  
Soil Erosion Modeling ◽  
Support Practices ◽  
P Factor ◽  
Processing Techniques

Support practices (SPs) influence the magnitude of soil loss and can be readily influenced by human interventions to mitigate soil loss. The SPs factor is expressed as the P-factor in the widely used soil erosion model – the universal soil loss equation (USLE) – and its revised version. Although the effects of SPs on soil erosion are well recognized, the quantification of the P-factor for soil loss modeling remains challenging. This limitation of the P-factor particularly restricts the applicability of USLE-based models at large scales. Here, we analyzed the P-factor values in USLE-based models from 196 published articles. The results were as follows: (a) an increasing trend in the number of studies has been observed in recent years, especially at large scales; (b) the P-factor values for paddy fields, orchards, and croplands were 0.16 ± 0.15, 0.47 ± 0.12, and 0.49 ± 0.21, respectively, and in terms of different types of SPs, the P-factor values for terracing, contouring, and strip-cropping were 0.28 ± 0.18, 0.52 ± 0.24, and 0.49 ± 0.28, respectively; (c) various methods have been developed for P-factor qualification, although the methods that consider SP conditions were most frequently used in studies with relatively smaller areas (< 100 km2), suggesting that USLE-based models are in need of improvement via the quantification of the P-factor, particularly with respect to the regional and global scale; and (d) further improvements of the P-factor for soil erosion modeling should concentrate on building P-factor datasets at the regional level according to data on the effectiveness of SPs on soil loss control based on field experiments in published articles, using advanced image processing techniques based on higher-resolution satellite imagery and developing proxy indicators for P-factors at large scales.

scholarly journals Geo-Information Modeling of Soil Erosion for Sustainable Agriculture Land Management in Sambhunath Municipality

2020 ◽  
Vol 20 (1) ◽  
pp. 47-57
Author(s):  
Bikash Karma Karna ◽  
Shobha Shrestha ◽  
Hriday Lal Koirala
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Use Planning ◽  
Land Surface ◽  
Soil Loss ◽  
Management Practices ◽  
Information Science ◽  
Agricultural Land ◽  
Information Modeling ◽  
Total Potential

Geo-information science has attempted to estimate the actual soil loss and its correlative interpretation with land use and cover types in an agricultural land, Sambhunath Municipality. Among several empirical and physically based soil erosion models, Revised Universal Soil Loss Equation (RUSLE) are widely used and employed to estimate soil loss based on rainfall, topographic contour, and soil map. The soil erosion ranges values are found from 0 to 2635 t ha-1 yr-1 in terms of soil loss per year in the municipality. Soil erosion rates are found highly correlated with the increasing exposure of land surface in Chure range mostly on forest area. Agriculture lands spatially concentrated in 51.70% of the Municipality extent, is contributing significantly as of 16293 t ha-1 yr-1 of the total potential soil loss from fertile cropland. Based on severity of soil loss, cultivation agriculture areas are priority for reducing soil loss for optimum agriculture management practices in land use planning.

Sign in / Sign up

Export Citation Format

Share Document