scholarly journals A Review of the Science and Logic Associated with Approach Used in the Universal Soil Loss Equation Family of Models

Soil Systems ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 62 ◽  
Author(s):  
Kinnell
Keyword(s):  
Soil Loss ◽  
Agricultural Land ◽  
Universal Soil Loss Equation ◽  
Physical Situation ◽  
Rill Erosion ◽  
The Impact ◽  
Soil Losses ◽  
Soil Loss Equation ◽  
Rainfall Erosion

Soil erosion caused by rain is a major factor in degrading agricultural land, and agricultural practices that conserve soil should be used to maintain the long-term sustainability of agricultural land. The Universal Soil Loss Equation (USLE) was developed in the 1960s and 1970s to predict the long-term average annual soil loss from sheet and rill erosion on field-sized areas as an aid to making management decisions to conserve soil. The USLE uses six factors to take account of the effects of climate, soil, topography, crops, and crop management, and specific actions designed to conserve soil. Although initially developed as an empirical model based on data from more than 10,000 plot years of data collected in plot experiments in the USA, the selection of the independent factors used in the model was made taking account of scientific understanding of the drivers involved in rainfall erosion. In addition, assumptions and approximations were needed to make an operational model that met the needs of the decision makers at that time. Those needs have changed over time, leading to the development of the Revised USLE (RUSLE) and a second version of that, the Revised USLE, Version 2 (RUSLE2). While the original USLE model was not designed to predict short-term variations in erosion well, these developments have involved more use of conceptualization in order to deal with the time-variant impacts of the drivers involved in rainfall erosion. The USLE family of models is based on the concept that the “unit” plot, a bare fallow area 22.1 m long on a 9% slope gradient with cultivation up and down the slope, provides a physical situation where the effect of climate and soil on rainfall erosion can be determined without the need to consider the impact of the four other factors. The science and logic associated with this approach is reviewed. The manner by which the soil erodibility factor is determined from plot data ensures that the long-term average annual soil loss for the unit plot is predicted well, even when the assumption that event soil loss is directly related to the product of event rainfall energy, and the maximum 30-min intensity is not wholly appropriate. RUSLE2 has a capacity to use CLIGEN, the weather generator used in WEPP, and so can predict soil losses based on individual storms in a similar way to WEPP. Including a direct consideration of runoff in determining event erosivity enhances the ability to predict event soil losses when runoff is known or predicted well, but similar to more process-based models, this ability is offset by the difficulty in predicting runoff well.

COMPARISON OF PREDICTED AND MEASURED SHEET AND RILL EROSION LOSSES IN SOUTHERN ONTARIO

1979 ◽  
Vol 59 (2) ◽  
pp. 211-213 ◽  
Author(s):  
L. J. P. VAN VLIET ◽  
G. J. WALL
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Rill Erosion ◽  
Southern Ontario ◽  
Loss Data ◽  
Soil Losses ◽  
Runoff Plots ◽  
Soil Loss Equation

Sheet and rill erosion losses evaluated by the universal soil loss equation were compared with 4–6 yr of measured soil loss data from runoff-plots at two locations in southern Ontario. Results indicated no significant differences (P = 0.10) between predicted and measured soil losses.

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 Erosion Assessment Modeling Using the Sateec Gis Model on the Prislop Catchment

2014 ◽  
Vol 8 (1) ◽  
pp. 217-224
Author(s):  
Gheorghe Damian ◽  
Daniel Năsui ◽  
Floarea Damian ◽  
Dan Ciurte
Keyword(s):  
Soil Loss ◽  
Assessment Tool ◽  
Universal Soil Loss Equation ◽  
Rill Erosion ◽  
Erosion Modeling ◽  
Gis Model ◽  
Sediment Assessment ◽  
Arcview Gis ◽  
Gully Head ◽  
Soil Loss Equation

Abstract The Sediment Assessment Tool for Effective Erosion Control (SATEEC) acts as an extension for ArcView GIS 3, with easy to use commands. The erosion assessment is divided into two modules that consist of Universal Soil Loss Equation (USLE) for sheet/rill erosion and the nLS/USPED modeling for gully head erosion. The SATEEC erosion modules can be successfully implemented for areas where sheet, rill and gully erosion occurs, such as the Prislop Catchment. The enhanced SATEEC system does not require experienced GIS users to operate the system therefore it is suitable for local authorities and/or students not so familiar with erosion modeling.

scholarly journals Modeling of water erosion by the erosion potential method in a pilot subbasin in southern Minas Gerais

2019 ◽  
Vol 40 (2) ◽  
pp. 555 ◽  
Author(s):  
André Silva Tavares ◽  
Velibor Spalevic ◽  
Junior Cesar Avanzi ◽  
Denismar Alves Nogueira ◽  
Marx Leandro Naves Silva ◽  
...  
Keyword(s):  
Soil Loss ◽  
Water Erosion ◽  
Minas Gerais ◽  
Universal Soil Loss Equation ◽  
Southeastern Brazil ◽  
Erosion Processes ◽  
Total Soil ◽  
The Mean ◽  
Soil Losses ◽  
Soil Loss Equation

Soil losses due to water erosion threaten the sustainability of agriculture and the food security of current and future generations. This study estimated potential soil losses and sediment production under different types of land uses in a subbasin in the Municipality of Alfenas, southern Minas Gerais, southeastern Brazil. The objective of this research was to evaluate the application of the Potential Erosion Method by the Intensity of Erosion and Drainage program and correlate the findings with the results obtained by the Revised Universal Soil Loss Equation as well as geoprocessing techniques and statistical analyses. In the Potential Erosion Method, the coefficient indicating the mean erosion intensity was 0.37, which corresponded to erosion category IV and indicated weak laminar erosion processes, and the total soil loss was 649.31 Mg year-1 and the mean was 1.46 Mg ha-1 year-1. These results were consistent in magnitude with those obtained in the Revised Universal Soil Loss Equation, which estimated a mean soil loss of 1.52 Mg ha-1 year-1 and a total soil loss of 668.26 Mg year-1. The Potential Erosion Method suggests that 1.5% of the area presents potential soil losses above the soil loss tolerance limit, which ranged from 5.19 to 5.90 Mg ha-1 year-1, while the Revised Universal Soil Loss Equation indicated that 7.3% of the area has potential soil losses above the limit. The maximum sediment discharge was 60 Mg year-1, meaning that 9.3% of the total soil loss reached the depositional areas of the river plains or watercourses. The Potential Erosion Method was efficient in the evaluation of water erosion in tropical soils, and the results were consistent with models widely employed in the estimation of soil losses. Thus, the model can support the evaluation of soil losses in Brazil and is a robust tool for evaluating the sustainability of agricultural activities.

scholarly journals Development Land Erosion Model Using Model Builder GIS (Case Study: Citepus Watershed)

2018 ◽  
Vol 147 ◽  
pp. 03003
Author(s):  
Dina PA Hidayat ◽  
Sih Andajani
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Model Builder ◽  
Watershed Analysis ◽  
Runoff Discharge ◽  
The Impact ◽  
Impervious Areas ◽  
Soil Loss Equation

Land erosion is the impact of increasing runoff discharge and land use conversion to impervious areas. Land erosion usually calculated by formula called USLE (Universal Soil Loss Equation) then modified as MUSLE (Modified Universal Soil Loss Equation). These formula calculate average annual soil loss in tons/areas depends on rainfall erosivity (R), soil erodibility factor (K), topographic factor (LS), cropping and conservation factor (CP). GIS (Geographic Information System) is a system designed to capture, manipulate, and analyze spatial/geographic data. There are some tools related water resources analysis in ArcGIS such as: watershed analysis and also have a tools for user to create their own model called model builder. This research was aim to create a model to calculate land erosion using MUSLE formula by model builder in ArcGIS. The output for this research is the model which can be used to calculate annual soil loss in watershed area based on GIS systems. For the model trial and case study, we use Citepus watershed located on Bandung West Java, that has 5 river branches: Cibogo, Cikakak, Cilimus, Cipedes and Ciroyom. As the result of the model, the value of average annual soil loss in Citepus watershed can be calculated automatically by developed model.

scholarly journals Socioeconomic modifications of the universal soil loss equation

Solid Earth ◽  
2015 ◽  
Vol 6 (3) ◽  
pp. 1025-1035 ◽  
Author(s):  
A. Erol ◽  
Ö. Koşkan ◽  
M. A. Başaran
Keyword(s):  
Socioeconomic Factors ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Physical Factors ◽  
Simulation Methods ◽  
Human Influence ◽  
Social Scientists ◽  
Socioeconomic And Demographic Factors ◽  
The Impact ◽  
Soil Loss Equation

Abstract. While social scientists have long focused on socioeconomic and demographic factors, physical modelers typically study soil loss using physical factors. In the current environment, it is becoming increasingly important to consider both approaches simultaneously for the conservation of soil and water, and the improvement of land use conditions. This study uses physical and socioeconomic factors to find a coefficient that evaluates the combination of these factors. It aims to determine the effect of socioeconomic factors on soil loss and, in turn, to modify the universal soil loss equation (USLE). The methodology employed in this study specifies that soil loss can be calculated and predicted by comparing the degree of soil loss in watersheds, with and without human influence, given the same overall conditions. A coefficient for socioeconomic factors, therefore, has been determined based on adjoining watersheds (WS I and II), employing simulation methods. Combinations of C and P factors were used in the USLE to find the impact of their contributions to soil loss. The results revealed that these combinations provided good estimation of soil loss amounts for the second watershed, i.e., WS II, from the adjoining watersheds studied in this work. This study shows that a coefficient of 0.008 modified the USLE to reflect the socioeconomic factors, such as settlement, influencing the amount of soil loss in the studied watersheds.

Event erosivity factor and errors in erosion predictions by some empirical models

Soil Research ◽  
2003 ◽  
Vol 41 (5) ◽  
pp. 991 ◽  
Author(s):  
P. I. A. Kinnell
Keyword(s):  
Empirical Model ◽  
Soil Loss ◽  
High Capacity ◽  
Soil Surface ◽  
Large Degree ◽  
Empirical Models ◽  
Universal Soil Loss Equation ◽  
Erosivity Index ◽  
Soil Losses ◽  
Soil Loss Equation

Analyses undertaken in this paper show that the Universal Soil Loss Equation (USLE) tends to overestimate low values of soil loss when the soil surface has a high capacity to infiltrate rainfall, but the degree of overestimation falls as the capacity of the soil to produce runoff increases. The USLE-M, a version of the USLE that uses the product of the runoff ratio and the EI30 as the event erosivity index, is more efficient in estimating soil loss because runoff is considered explicitly in the event erosivity index, whereas it is not in the USLE. The results show clearly that the problem of the USLE and the RUSLE overpredicting observed erosion losses, when erosion losses are low, is related to a large degree to model formula. In addition, the removal of restrictions to what constitutes a valid EI30 value increases the capacity of the RUSLE to overpredict low soil losses. As the USLE is an empirical model, values of USLE K, C, and P can only be used when the event erosivity parameter is EI30. Models like EPIC ignore this fact.

scholarly journals Spatial Analysis of Erosion and Quantification of Soil Losses in Western Algeria

2021 ◽  
Vol 40 (2) ◽  
pp. 130-136
Author(s):  
Benamar Belgherbi ◽  
Kheloufi Benabdeli
Keyword(s):  
Spatial Analysis ◽  
Soil Loss ◽  
Significant Loss ◽  
Universal Soil Loss Equation ◽  
The South ◽  
Flat Terrain ◽  
Erosion Models ◽  
Western Algeria ◽  
Soil Losses ◽  
Soil Loss Equation

Abstract The objective of this study is to establish a soil loss map of a region located in western Algeria allowing the spatialization of erosion models, deposition, and quantification of soil loss. The model applied is Universal Soil Loss Equation (USLE), wich was developed by Wischmeier and Smith. The map of current soil losses derived from it shows five areas: very low, low, medium, strong, and very strong. The significant loss in soil areas is located in most of the south of the area, the upstream mountains part, and a portion to the northwest of the region. They cover an area of 16,805 ha (15.27%) of the study area. The remainder of area constituting unrigged flat terrain accounts for a loss in low soil. The latter receives all the solid contributions which are deposited there constituting an important deposit.

scholarly journals Analysis of the Influence of DTM Source Data on the LS Factors of the Soil Water Erosion Model Values with the Use of GIS Technology

2021 ◽  
Vol 13 (4) ◽  
pp. 678
Author(s):  
Anna Fijałkowska
Keyword(s):  
Soil Water ◽  
Soil Loss ◽  
Water Erosion ◽  
Universal Soil Loss Equation ◽  
Gis Technology ◽  
Geographical Regions ◽  
Elevation Data ◽  
Topographical Factors ◽  
The Impact ◽  
Soil Loss Equation

Counteracting soil degradation is one of the strategic priorities for sustainable development. One of the most important current challenges is effective management of available resources. Multiple studies in various aspects of soil water erosion are conducted in many research institutions in the world. They concern, among others, the development of risk estimation models and the use of new data for modelling. The aim of the presented research was a discussion on the impact of the accuracy and detail of elevation data sources on the results of soil water erosion topographic factors modelling. Elevation data for this research were chosen to reflect various technologies of data acquisition, differences in the accuracy and detail of field forms mapping and, consequently, the spatial resolution of the digital terrain models (DTMs). The methodology of the universal soil loss equation USLE/RUSLE was used for the L and S factors modelling and calculation. The research was carried out in three study areas located in different types of geographical regions in Poland: uplands, highlands and lake districts. The proposed methodology consisted of conducting detailed comparative elevation and slope value assessments, calculating the values of topographical factors of the universal soil loss equation: slope length (L) and slope (S) and a detailed analysis of the total LS factors values. An approach to assess LS factors values within homogeneous areas such as agricultural plots has also been proposed. The studies draw the conclusion that the values of topographical factors obtained from various DTM sources were significantly different. It was shown that the choice of the right modelling data has a significant impact on the L and S factors values and, thus, also, on the decision-making process. The conducted research has definitely shown that data of the highest accuracy and detail should be used to study local phenomena (inter alia erosion), even analysing a large area.

scholarly journals Socio-economic modifications of the Universal Soil Loss Equation

2015 ◽  
Vol 7 (2) ◽  
pp. 1731-1759
Author(s):  
A. Erol ◽  
Ö. Koşkan ◽  
M. A. Başaran
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Physical Factors ◽  
Economic Factors ◽  
Simulation Methods ◽  
Human Influence ◽  
Social Scientists ◽  
The Impact ◽  
Soil Loss Equation ◽  
Socio Economic Factors

Abstract. While social scientists have long focused on socio-economic and demographic factors, physical modelers typically study soil loss using physical factors. In the current environment, it is becoming increasingly important to consider both approaches simultaneously for the conservation of soil and water, and the improvement of land use conditions. This study uses physical and socio-economic factors to find a coefficient that evaluates the combination of these factors. It aims to determine the effect of socio-economic factors on soil loss and, in turn, to modify the Universal Soil Loss Equation (USLE). The methodology employed in this study specifies that soil loss can be calculated and predicted by comparing the degree of soil loss in watersheds, with and without human influence, given the same overall conditions. A coefficient for socio-economic factors, therefore, has been determined based on adjoining watersheds (WS I and II), employing simulation methods. Combinations of C and P factors were used in the USLE to find the impact of their contributions on soil loss. The results revealed that these combinations provided good estimation of soil loss amounts for the second watershed, i.e. WS II, from the adjoining watersheds studied in this work. This study shows that a coefficient of 0.008 modified the USLE to reflect the socio-economic factors as settlement influencing the amount of soil loss in the watersheds studied.

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