Rapid Assessment of Soil Erosion in the Rio Lempa Basin, Central America, Using the Universal Soil Loss Equation and Geographic Information Systems

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.

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Comparison of different approaches to LS factor calculations based on a measured soil loss under simulated rainfall.

Soil and Water Research ◽

10.17221/222/2015-swr ◽

2017 ◽

Vol 12 (No. 2) ◽

pp. 69-77 ◽

Cited By ~ 9

Author(s):

M. Hrabalíková ◽

M. Janeček

Keyword(s):

Information Systems ◽

Geographic Information Systems ◽

Soil Erosion ◽

Soil Loss ◽

Geographic Information ◽

Experimental Plot ◽

Simulated Rainfall ◽

Slope Length ◽

Digital Elevation ◽

Elevation Model

Geographic Information Systems (GIS) in combination with soil loss models can enhance evaluation of soil erosion estimation. SAGA and ARC/INFO geographic information systems were used to estimate the topographic (LS) factor of the Universal Soil Loss Equation (USLE) that in turn was used to calculate the soil erosion on a long-term experimental plot near Prague in the Czech Republic. To determine the influence of a chosen algorithm on the soil erosion estimates a digital elevation model with high accuracy (1 × 1 m) and a measured soil loss under simulated rainfall were used. These then provided input for five GIS-based and two manual procedures of computing the combined slope length and steepness factor in the (R)USLE. The results of GIS-based (R)USLE erosion estimates from the seven procedures were compared to the measured soil loss from the 11 m long experimental plot and from 38 rainfall simulations performed here during 15 years. The results indicate that the GIS-based (R)USLE soil loss estimates from five different approaches to calculation of LS factor are lower than the measured average annual soil loss. The two remaining approaches over-predicted the measured soil loss. The best method for LS factor estimation on field scale is the original manual method of the USLE, which predicted the average soil loss with 6% difference from the measured soil loss. The second method is the GIS-based method that concluded a difference of 8%. The results of this study show the need for further work in the area of soil erosion estimation (with particular focus on the rill/interrill ratio) using the GIS and USLE. The study also revealed the need for an application of the same approach to catchment area as it might bring different outcomes.

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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.

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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.

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