Integrated universal soil loss equation (USLE) and Geographical Information System (GIS) for soil erosion estimation in A Sap basin: Central Vietnam

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.

Download Full-text

Soil Erosion Risk Assessment and Spatial Mapping in Jhagrabaria Watershed, Allahabad, U.P. (India) by Using LANDSAT 7ETM+ Remote Sensing Data, Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS)

Advances in Geographical and Environmental Sciences - Landscape Ecology and Water Management ◽

10.1007/978-4-431-54871-3_15 ◽

2014 ◽

pp. 205-219 ◽

Cited By ~ 2

Author(s):

K. S. Rawat ◽

A. K. Mishra ◽

V. K. Sehgal ◽

R. Bhattacharyya

Keyword(s):

Remote Sensing ◽

Risk Assessment ◽

Information System ◽

Soil Erosion ◽

Soil Loss ◽

Remote Sensing Data ◽

Geographical Information ◽

Spatial Mapping ◽

Erosion Risk ◽

Soil Loss Equation

Download Full-text

Numerical Modelling of Soil Erosion on Cephalonia Island, Greece Using Geographical Information Systems and the Revised Universal Soil Loss Equation (RUSLE)

Proceedings ◽

10.3390/proceedings2110618 ◽

2018 ◽

Vol 2 (11) ◽

pp. 618

Author(s):

Michail Xanthakis ◽

Panagiotis Minetos ◽

Georgia Lisitsa ◽

Georgia Kamari

Keyword(s):

Soil Erosion ◽

Forest Fires ◽

Soil Loss ◽

Geographical Information Systems ◽

Agricultural Sector ◽

Degradation Process ◽

Universal Soil Loss Equation ◽

Geographical Information ◽

Year 2000 ◽

Soil Loss Equation

Soil erosion on Cephalonia Island, Greece has been identified as a predominating land degradation process and a major threat to the sustainability of the agricultural sector. In the present work, the evolution of soil erosion on the island was estimated for the years 2000 and 2012. A simple empirical model, the Revised Universal Soil Loss Equation (RUSLE) for modeling soil erosion, was applied in a Geographical Information System (GIS). The results indicate that the mean annual soil erosion was estimated to be 12.78 t/ha for the year 2000 and 12.28 t/ha for the year 2012. Further, 38.24% of the area of Cephalonia demonstrated moderate to significantly high soil erosion in the year 2012 compared to 40.55% in year 2000. We can assume that during the period 2000–2012, despite influences on the natural environment including forest fires and overgrazing, the combination of vegetation and other protective soil factors contributed to reducing soil erosion.

Download Full-text

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

10.22541/au.160946369.92099648/v1 ◽

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.

Download Full-text

Estimation of Soil Erosion using USLE and GIS

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1646.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 3936-3939

Keyword(s):

Information System ◽

Geographic Information System ◽

Soil Erosion ◽

Soil Loss ◽

Erosion Rate ◽

Environmental Problem ◽

Gis Technique ◽

Economic Imbalances ◽

Factor C ◽

Soil Loss Equation

Soil erosion is one of the most serious environmental problem which must be taken in to consideration to prevent economic imbalances in nature. Soil erosion not only affect the agricultural productivity but also increases level of sedimentation. The study was carried out to determine the soil erosion for the watershed which is located in Godavari middle sub basin, Nanded district, Maharashtra state (India). The universal soil loss equation (USLE) and Geographic information system (GIS) technique was used to determine soil erosion. Present study revealed that, the study area is under moderate erosion with an average soil loss 7.233 tones/ha/yr. Where as minimum and maximum erosion rate observed as 5.39 tones/ha/yr to 10.27 tones/ha/yr respectively. The various maps of USLE factors prepared in QGIS environment. Statistically significant relationship obtained between soil loss and cover management factor (C). It was observed that C factor more influences in soil loss than any other factor.

Download Full-text

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

Journal of Southwest Jiaotong University ◽

10.35741/issn.0258-2724.55.3.19 ◽

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.

Download Full-text