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.

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 A review of soil erosion modeling by R/USLE in Morocco: Achievements and limits

2021 ◽  
Vol 234 ◽  
pp. 00067
Author(s):  
Mohamed Manaouch ◽  
Anis Zouagui ◽  
Imad Fenjiro
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Review Paper ◽  
Empirical Models ◽  
Universal Soil Loss Equation ◽  
Erosion Modeling ◽  
Future Studies ◽  
Current Concerns ◽  
Soil Erosion Assessment ◽  
Soil Loss Equation

Soil erosion is a major cause of land degradation. It can be estimated with several models, such as empirical, conceptual and physical based. One of the empirical models used worldwide nowadays for soil erosion assessment is the Universal Soil Loss Equation (USLE) and its updated form, the Revised Universal Soil Loss Equation (RUSLE). In Morocco, this model is being used to assess and quantify soil loss by water erosion. In spite of this, it was noted that limited studies employed correctly this important tool. The goal of this review paper was to identify potential usage of R/USLE models in Morocco. This was done by evaluating the conducted studies concerning these models and main gaps and challenges were determined accordingly. Improvement options and future requirements for using R/USLE models were recommended. In order to assess the statues of the R/USLE models applications, the 56 published documents related to R/USLE models conducted in Morocco during the first use till 2020 were collected and reviewed. These publications covered five main areas. The main benefits as well as gaps of the conducted studies were discussed for each area. Current concerns, need of future studies as well as related recommendations and suggestions were also presented.

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 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.

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 ASSESSMENT AND MAPPING OF RAINFALL EROSIVITY INDEX (R) FOR MAJHA REGION, PUNJAB IS A STATE IN NORTHERN, INDIA

2021 ◽  
Vol 9 (3) ◽  
pp. 15-23
Author(s):  
Prashant Kumar
Keyword(s):  
Cover Crop ◽  
Soil Loss ◽  
Management Practices ◽  
Rainfall Intensity ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Northern India ◽  
Close Observation ◽  
Erosivity Index ◽  
Soil Loss Equation

Purpose: This study gives a critical assessment of the rainfall erosivity factor (R) for selected sites in the Majha region, representing different locations use of mean monthly rainfall data.  Methodology: By applying empirical methods, the rainfall intensity for all the locations were obtained and was further determined at three different intervals of 30-minutes, 45-minutes and 60-minutes, respectively. The rainfall erosivity factor (R) was calculated by the revised universal soil loss equation (RUSLE). Main Findings: Using RUSLE, the rainfall erosivity factor (R) for each of the locations was measured as follows; EI = 3878.49 (MJmmha-1hr-1), EI = 4013.71 (MJmmha-1hr-1), EI = 4302.24 (MJmmha-1hr-1) for Majha region of Amritsar, Tarntaran and Pathankot respectively. A close observation of the data obtained revealed that as rainfall intensity increased with the duration, the rainfall erosivity index reduced or decreased. Implications of study: Nevertheless, it is expected that if proper cover crop and management practices are applied despite the region, the study area falls within, rainfall erosivity can be cushioned, thus reducing further erosion tendencies and enhancing food production chances from productive lands within the area. The novelty of study: The rainfall erosivity factor (R) was calculated by the revised universal soil loss equation (RUSLE).

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.

Laboratory methods for measurement of soil erodibilities (K-factors) for the universal soil loss equation

Soil Research ◽  
1992 ◽  
Vol 30 (2) ◽  
pp. 233 ◽  
Author(s):  
RJ Loch ◽  
CJ Rosewell
Keyword(s):  
Particle Size ◽  
Soil Loss ◽  
Laboratory Data ◽  
Soil Surface ◽  
Field Measurements ◽  
Average Density ◽  
Universal Soil Loss Equation ◽  
Particle Sizes ◽  
Size Distributions ◽  
Soil Loss Equation

This paper reports a comparison of several methods for estimating the K (erodibility) factor for the Universal Soil Loss Equation (USLE) on the basis of laboratory measurements of soil properties. All methods used the nomograph of Wischmeier et al. (J. Soil Water Cons., 1971, 26, 189-93) to calculate K on the basis of laboratory data, but the data inputs ranged from: dispersed particle sizes as originally used in the nomograph; non-dispersed particle size, measured after shaking in water; and equivalent sand size distributions, based on settling velocity distributions of particles (aggregates and sand grains) at the soil surface under rain. A further method tested with the use of aggregated particle sizes resulting from rainfall wetting was a correction of the calculated K based on average density of wet sediment >0.100 mm diameter. Estimated K factors were compared with K factors derived from field measurements of soil loss for five soils. Use of dispersed particle sizes gave poor prediction of field K values for the three clay soils, and size distributions measured after rainfall wetting gave poor predictions of field K values for the four soils that had sediment of low density. Predictions of K from the use of non-dispersed particle sizes, and from the use of particle size at the soil surface under rain combined with a correction for sediment density were good for three soils, reasonable for one, and little different to that from the nomograph for the remaining soil. These latter two methods gave similar results, and were successful in predicting field values of K. As well, both methods appear to be sensitive to effects of cropping management on soil structure and erodibility. Either method could be used, depending on laboratory resources available and possible other uses of the data obtained. Simpler methods for measuring size distributions after rainfall wetting and for estimating sediment density are suggested.

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