scholarly journals Modeling Soil Erosion and Landscape Metric Analysis of River Catchments in Pulau Pinang, Malaysia

2020 ◽  
Vol 55 (3) ◽  
Author(s):  
Sumayyah Aimi Mohd Najib
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Diversity Index ◽  
Land Use Changes ◽  
Shannon Diversity Index ◽  
Universal Soil Loss Equation ◽  
Data Sampling ◽  
Shannon Diversity ◽  
Soil Loss Equation

To determine the soil erosion in ungauged catchments, the author used 2 methods: Universal Soil Loss Equation model and sampling data. Sampling data were used to verify and validate data from model. Changing land use due to human activities will affect soil erosion. Land use has changed significantly during the last century in Pulau Pinang. The main rapid changes are related to agriculture, settlement, and urbanization. Because soil erosion depends on surface runoff, which is regulated by the structure of land use and brought about through changes in slope length, land-use changes are one of many factors influencing land degradation caused by erosion. The Universal Soil Loss Equation was used to estimate past soil erosion based on land uses from 1974 to 2012. Results indicated a significant increase in three land-use categories: forestry, built-up areas, and agriculture. Another method to evaluate land use changes in this study was by using landscape metrics analysis. The mean patch size of built-up area and forest increased, while agriculture land use decreased from 48.82 patches in 1974 to 22.46 patches in 2012. Soil erosion increased from an estimated 110.18 ton/km2/year in 1974 to an estimated 122.44 ton/km2/year in 2012. Soil erosion is highly related (R2 = 0.97) to the Shannon Diversity Index, which describes the diversity in land-use composition in river basins. The Shannon Diversity Index also increased between 1974 and 2012. The findings from this study can be used for future reference and for ungauged catchment research studies.

scholarly journals Application of Revised Universal Soil Loss Equation (Rusle) Model to Assess Soil Erosion in “Kalu Ganga” River Basin in Sri Lanka

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
D. L. D. Panditharathne ◽  
N. S. Abeysingha ◽  
K. G. S. Nirmanee ◽  
Ananda Mallawatantri
Keyword(s):  
Land Use ◽  
Sri Lanka ◽  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Management Practices ◽  
Agricultural Land ◽  
Universal Soil Loss Equation ◽  
Rusle Model ◽  
Soil Loss Equation

Soil erosion is one of the main forms of land degradation. Erosion contributes to loss of agricultural land productivity and ecological and esthetic values of natural environment, and it impairs the production of safe drinking water and hydroenergy production. Thus, assessment of soil erosion and identifying the lands more prone to erosion are vital for erosion management process. Revised Universal Soil Loss Equation (Rusle) model supported by a GIS system was used to assess the spatial variability of erosion occurring at Kalu Ganga river basin in Sri Lanka. Digital Elevation Model (30 × 30 m), twenty years’ rainfall data measured at 11 rain gauge stations across the basin, land use and soil maps, and published literature were used as inputs to the model. The average annual soil loss in Kalu Ganga river basin varied from 0 to 134 t ha−1 year−1 and mean annual soil loss was estimated at 0.63 t ha−1 year−1. Based on erosion estimates, the basin landscape was divided into four different erosion severity classes: very low, low, moderate, and high. About 1.68% of the areas (4714 ha) in the river basin were identified with moderate to high erosion severity (>5 t ha−1 year−1) class which urgently need measures to control soil erosion. Lands with moderate to high soil erosion classes were mostly found in Bulathsinghala, Kuruwita, and Rathnapura divisional secretarial divisions. Use of the erosion severity information coupled with basin wide individual RUSLE parameters can help to design the appropriate land use management practices and improved management based on the observations to minimize soil erosion in the basin.

scholarly journals Soil erodibility indices under different land uses in Ri-Bhoi district of Meghalaya (India)

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Manish Olaniya ◽  
Pradip Kumar Bora ◽  
Susanta Das ◽  
Pukhrambam Helena Chanu
Keyword(s):  
Land Use ◽  
Organic Matter ◽  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Soil Erodibility ◽  
Land Uses ◽  
Modified Clay ◽  
K Index ◽  
Soil Loss Equation

Abstract In absence of soil erosion plots for determination of erodibility index (K) for erosion models like Universal Soil Loss Equation (USLE) or Revised Universal Soil Loss Equation (RUSLE) to estimate soil erosion, empirical relations are used. In the present study, soil erodibility index was determined for entire Ri-bhoi district of Meghalaya based on soil physical and chemical properties through empirical relationship and presented in a map form. Dominant land uses of the district were identified through geo-spatial tools which were viz. agriculture, forest, jhum land and wasteland. Soil samples from surface depth (01–15 cm) were collected from areas of different dominant land uses. Twenty five sampling points were selected under each land use type and geo-coded them on the base map of Ri-bhoi district. Apart from K-index, Clay Ratio, Modified Clay Ratio and Critical Soil Organic Matter were also determined for understanding the effect of primary soil particles on erodibility. In agriculture land use system K-index values were found in the range of 0.08–0.41 with an average of 0.25 ± 0.02. In case of jhum, forest and wasteland these were in the range of 0.08–0.42 with an average of 0.20 ± 0.01; 0.09–0.40 with an average of 0.22 ± 0.02, and 0.10–0.34 with an average value of 0.23 ± 0.02, respectively. Clay ratio (2.74) and Modified clay ratio (2.41) were observed to be higher in forest LUS, lower clay ratio (1.97) and modified clay ratio (1.81) were found in the wasteland indicating erosion susceptibility in forested area. The values of Critical Level of Organic Matter (CLOM) for the district ranged from 4.72 to 16.56. Out of 100 samples, only one sample had CLOM value less than 5 and rest 99 samples had values more than 5 indicating that the soils of the district had moderate to stable soil structure and offer resistance to erosion. All the indices values of geo-coded points were then interpolated in the Arc-GIS environment to produce land use based maps for Ri-bhoi district of Meghalaya. As K-index is a quantitative parameter which is used in models, the index can be then interpolated for estimation of soil erosion through USLE or RUSLE for any given situation.

scholarly journals Soil erosion estimation using Geographic Information System (GIS) and Revised Universal Soil Loss Equation (RUSLE) in the Siwalik Hills of Nawalparasi, Nepal

2021 ◽  
Author(s):  
Durga Bahadur Tiruwa ◽  
Babu Ram Khanal ◽  
Sushil Lamichhane ◽  
Bharat Sharma Acharya
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Geographic Information ◽  
Universal Soil Loss Equation ◽  
Conservation Practices ◽  
Erosion Hotspots ◽  
Soil Loss Equation

Abstract Soil erosion is one of the gravest environmental threats to the mountainous ecosystems of Nepal. Here, we combined a Geographic Information System (GIS) with the Revised Universal Soil Loss Equation (RUSLE) to estimate average annual soil loss, map erosion factors, compare soil erosion risks among different land use types, and identify erosion hotspots and recommend land use management in the Girwari river watershed of the Siwalik Hills. The annual soil loss was estimated using RUSLE factors: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover crops (C), and conservation practices (P), and erosion factors maps were generated using GIS. Results indicate highest total erosion occurring in hill forests (13,374.3 t yr–1) and lowest total erosion occurring in grasslands (2.9 t yr–1). Hill forests showed high to very severe erosion due to steepness of hills, open forest types, and minimal use of conservation practices. Also, erosion hotspots (>15 t ha–1 yr–1) occurred in only 4.2% of the watershed, primarily in steep slopes. Overall, these results provide important guidelines to formulate management plans and informed decisions on soil conservation at local to regional levels. While the study is the first effort to assess soil erosion dynamics in the Girwari river watershed, potential for application in other basins largely exists.

scholarly journals Evaluation of Soil Erosion and Sustainable Land Use Management in the Sarısu Basin

2017 ◽  
Vol 5 (8) ◽  
pp. 864
Author(s):  
Ertuğrul Karaş ◽  
İrfan Oğuz
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Equation Model ◽  
Universal Soil Loss Equation ◽  
Land Use Management ◽  
Starting Point ◽  
Soil Losses ◽  
Soil Loss Equation

Land use management requires controlling natural resources for sustainability. Soil erosion related to improper land use is a major issue around the world. Land degradation may harm the health of ecosystems. Defining the soil loss in a basin is the starting point in the restoration of soil quality for crop production. Reducing soil losses to a tolerable rate is one of the primary objectives for sustainability and soil conservation. Central Anatolia is under considerable risk due to an increase in the cultivation of marginal lands for food production. Cultivated lands have already been reached the final limits throughout the last 50 years. Moreover, forests and considerable areas of pasture have recently been converted to ploughed fields due to agricultural expansion. This study was conducted in the Sarısu basin to evaluate soil losses and land use management for sustainability. The Universal Soil Loss Equation model and Geographic Information System techniques were used to estimate the soil losses. The mean potential soil loss of the basin was calculated to be 1.88 t ha-1 per year with the Universal Soil Loss Equation model. These results are comparatively small when compared to the average value for Turkey of 13 t ha-1 yearly. Our calculated results are closer to the value for the Sakarya river basin, which is approximately 2.77 t ha-1 y-1. In this study, land usages in the Sarısu basin were evaluated in terms of soil losses, tolerable soil loss rates and soil conservation precautions.

scholarly journals Erosion and sedimentation analysis due to land use changes in the Krueng Pase watershed

2021 ◽  
Vol 922 (1) ◽  
pp. 012040
Author(s):  
Muntazar ◽  
Joni ◽  
I Ramli
Keyword(s):  
Land Use ◽  
Soil Loss ◽  
Negative Impact ◽  
Positive Impact ◽  
Land Use Changes ◽  
Appropriate Technology ◽  
Universal Soil Loss Equation ◽  
Erosion Hazard ◽  
Land Management System ◽  
Soil Loss Equation

Abstract Human interactions with watershed can have positive and negative impact. The positive impact can improve socio-economic conditions. However, the negative impact is the degradation of the watershed function. For example, it’s continued increase in erosion rate on the land. The purpose of this study is to analyze erosion and sedimentation due to land use changes using the Universal Soil Loss Equation (USLE) and Modified Universal Soil Loss Equation (MUSLE) methods. Data collecting to determine erosion and sedimentation values are rainfall, soil erodibility and soil moisture, land use, and river water samples. The biggest decreased land use changes occurred in forest by 5.87%, followed by agriculture which decreased by 0.65% and water body 0.047%. On the other hand, built-up area increased by 0.65% and land used for agriculture increased by 6.15%. Furthermore, the level of erosion hazard in the Krueng Pase watershed from 2009 to 2019 increased in area, the mild level of erosion hazard increased by 7.9% and the moderate level erosion hazard by 27.4%. The amount of sedimentation obtained using the MUSLE method in 2019 was 6,869,98 tons and in 2009 was 41,692,97 tons. Erosion valuein 2019 is relatively small compared to other years. It’s really depends on the rainfall and the discharge that occurs. Therefore, a good land management system, proper and appropriate technology used, eco-hydrology concept and the monitoring of land use change regularly are needed, so damage that impact the Krueng Pase watershed can be prevented and minimize.

scholarly journals Estimation of annual soil erosion dynamics (2005 - 2015) in Pakistan using Revised Universal Soil Loss Equation (RUSLE)

2021 ◽  
Author(s):  
Hammad Gilani ◽  
Adeel Ahmad ◽  
Isma Younes ◽  
Sawaid Abbas
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Management Practices ◽  
Climatic Factors ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Conservation Practice ◽  
Administrative Units ◽  
Soil Loss Equation

Abrupt changes in climatic factors, exploitation of natural resources, and land degradation contribute to soil erosion. This study provides the first comprehensive analysis of annual soil erosion dynamics in Pakistan for 2005 and 2015 using publically available climatic, topographic, soil type, and land cover geospatial datasets at 1 km spatial resolution. A well-accepted and widely applied Revised Universal Soil Loss Equation (RUSLE) was implemented for the annual soil erosion estimations and mapping by incorporating six factors; rainfall erosivity (R), soil erodibility (K), slope-length (L), slope-steepness (S), cover management (C) and conservation practice (P). We used a cross tabular or change matrix method to assess the annual soil erosion (ton/ha/year) changes (2005-2015) in terms of areas and spatial distriburtions in four soil erosion classes; i.e. Low (<1), Medium (1–5], High (5-20], and Very high (>20). Major findings of this paper indicated that, at the national scale, an estimated annual soil erosion of 1.79 ± 11.52 ton/ha/year (mean ± standard deviation) was observed in 2005, which increased to 2.47 ±18.14 ton/ha/year in 2015. Among seven administrative units of Pakistan, in Azad Jammu & Kashmir, the average soil erosion doubled from 14.44 ± 35.70 ton/ha/year in 2005 to 28.03 ± 68.24 ton/ha/year in 2015. Spatially explicit and temporal annual analysis of soil erosion provided in this study is essential for various purposes, including the soil conservation and management practices, environmental impact assessment studies, among others.

scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

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