Recent advances in the assessment of soil erosion vulnerability in watersheds

Water induced soil erosion has always been a matter of concern in watersheds as they increase the soil vulnerability towards erosion. If unchecked, the eroded material reduces the capability of the river to carry the adequate amount of water and increase the amount of sediments in the watershed area. Determining vulnerability of soil to erosion plays a key role in identifying the extent of fragility and helps in making appropriate plans for conservation. Among various methods present to assess soil erosion vulnerability, there is a need to understand the frequently used methods so far and its advancement with time. Various models have been used in past two decades (1991-2019) and the Revised Universal Soil Loss Equation (RUSLE) is the most used model because of its quantitative ability to estimate the average annual soil loss due to erosion in a watershed and its compatibility with the GIS interface. Different approaches like MCDM, SWAT etc. are being utilised to study soil erosion vulnerability of watersheds. This review showed that the frequently used MCDM method is a Compound Factor (CF) method and that RUSLE is a most used quantitative approach. The review identifies 14 different methods which includes 4 methods which provide quantitative estimation while the other 10 methods are used for qualitative assessment of soil erosion vulnerability. Being the most adopted approach, various modifications of different factors of RUSLE introduced by researchers have made it more efficient with time. This review identifies the trend in advancement of various approaches and methods to study soil erosion vulnerability of watersheds around the world and also how various studies are distributed in the Himalayan and non-Himalayan region. The review also provides an understanding of the status of various current approaches to study soil erosion in a watershed and lists the improvements adopted in the frequently used approaches during 1991 and 2019.

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A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates

Hydrology and Earth System Sciences ◽

10.5194/hess-22-6059-2018 ◽

2018 ◽

Vol 22 (11) ◽

pp. 6059-6086 ◽

Cited By ~ 42

Author(s):

Rubianca Benavidez ◽

Bethanna Jackson ◽

Deborah Maxwell ◽

Kevin Norton

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Gully Erosion ◽

Data Availability ◽

Universal Soil Loss Equation ◽

Soil Productivity ◽

Temporal Scales ◽

Erosion Models ◽

The World ◽

Soil Loss Equation

Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape to address the problem strategically. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviews the different sub-factors of USLE and RUSLE, and analyses how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the strengths and limitations of the different equations are discussed, and guidance is given as to which equations may be most appropriate for particular climate types, spatial resolution, and temporal scale. We investigate some of the limitations of existing (R)USLE formulations, such as uncertainty issues given the simple empirical nature of the model and many of its sub-components; uncertainty issues around data availability; and its inability to account for soil loss from gully erosion, mass wasting events, or predicting potential sediment yields to streams. Recommendations on how to overcome some of the uncertainties associated with the model are given. Several key future directions to refine it are outlined: e.g. incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and compiling consistent units for the future literature to reduce confusion and errors caused by mismatching units. The potential of combining (R)USLE with the Compound Topographic Index (CTI) and sediment delivery ratio (SDR) to account for gully erosion and sediment yield to streams respectively is discussed. Overall, the aim of this paper is to review the (R)USLE and its sub-factors, and to elucidate the caveats, limitations, and recommendations for future applications of these soil erosion models. We hope these recommendations will help researchers more robustly apply (R)USLE in a range of geoclimatic regions with varying data availability, and modelling different land cover scenarios at finer spatial and temporal scales (e.g. at the field scale with different cropping options).

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A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

10.5194/hess-2018-68 ◽

2018 ◽

Cited By ~ 3

Author(s):

Rubianca Benavidez ◽

Bethanna Jackson ◽

Deborah Maxwell ◽

Kevin Norton

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Data Availability ◽

Water Bodies ◽

Universal Soil Loss Equation ◽

Soil Productivity ◽

Temporal Scales ◽

Erosion Models ◽

The World ◽

Soil Loss Equation

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Analysis of Ownership Data from Consolidated Land Threatened by Water Erosion in the Vlára Basin, Slovakia

Sustainability ◽

10.3390/su13010051 ◽

2020 ◽

Vol 13 (1) ◽

pp. 51

Author(s):

Alexandra Pagáč Mokrá ◽

Jakub Pagáč ◽

Zlatica Muchová ◽

František Petrovič

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Agricultural Land ◽

Water Erosion ◽

Land Consolidation ◽

Land Fragmentation ◽

Erosion Risk ◽

Definition Of ◽

The Relationship ◽

Soil Loss Equation

Water erosion is a phenomenon that significantly damages agricultural land. The current land fragmentation in Slovakia and the complete ambiguity of who owns it leads to a lack of responsibility to care for the land in its current condition, which could affect its sustainability in the future. The reason so much soil has eroded is obvious when looking at current land management, with large fields, a lack of windbreaks between them, and no barriers to prevent soil runoff. Land consolidation might be the solution. This paper seeks to evaluate redistributed land and, based on modeling by the Universal Soil Loss Equation (USLE) method, to assess the degree of soil erosion risk. Ownership data provided information on how many owners and what amount of area to consider, while taking into account new conditions regarding water erosion. The results indicate that 2488 plots of 1607 owners which represent 12% of the model area are still endangered by water erosion, even after the completion of the land consolidation project. The results also presented a way of evaluating the territory and aims to trigger a discussion regarding an unambiguous definition of responsibility in the relationship between owner and user.

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Effects of DEM resolutions on soil erosion prediction using Chinese Soil loss Equation

Geomorphology ◽

10.1016/j.geomorph.2021.107706 ◽

2021 ◽

pp. 107706

Author(s):

Ao Li ◽

X.C.(John) Zhang ◽

Baoyuan Liu

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Erosion Prediction ◽

Soil Loss Equation

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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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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.

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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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Estimating soil loss from a watershed in Western Deccan, India, using Revised Universal Soil Loss Equation

Landscape & Environment ◽

10.21120/le/10/1/2 ◽

2016 ◽

Vol 10 (1) ◽

pp. 13-25 ◽

Cited By ~ 5

Author(s):

Veena Joshi ◽

Nilesh Susware ◽

Debasree Sinha

Keyword(s):

Conservation Planning ◽

Soil Loss ◽

Tolerance Limit ◽

Design Tool ◽

Universal Soil Loss Equation ◽

The World ◽

Loss Models ◽

Gis Environment ◽

Semi Arid ◽

Soil Loss Equation

USLE (Universal Soil Loss Equation) is the original and the most widely accepted soil loss estimation technique till date which has evolved from a design tool for conservation planning to a research methodology all across the globe. The equation has been revised and modified over the years and became a foundation for several new soil loss models developed all around the world. The equation has been revised as RUSLE by Renard et al. (1991) and is computed in GIS environment. The Revised equation is landuse independent which makes it a useful technique to apply in a variety of environment. The present paper is an attempt to estimate soil loss from a semi-arid watershed in Western Deccan, India by employing RUSLE. The region is a rocky terrain and sediments are restricted to only a few localities. The result indicates that the region is at the threshold of soil tolerance limit.

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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

ENVIRONMENTAL SYSTEMS RESEARCH ◽

10.1186/s40068-020-00203-3 ◽

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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