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.

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 Estimativa da vulnerabilidade dos solos à erosão hídrica na bacia hidrográfica do Rio das Mortes (MG)

2021 ◽  
Vol 14 (1) ◽  
pp. e007659
Author(s):  
Jaíza Ribeiro Mota e Silva ◽  
Jéssica Assaid Martins Rodrigues ◽  
Luiz Fernando Coutinho de Oliveira ◽  
Marcelo Ribeiro Viola
Keyword(s):  
Soil Loss ◽  
Minas Gerais ◽  
Universal Soil Loss Equation ◽  
Soil Loss Equation

A erosão hídrica é uma das maiores causas de degradação dos solos no mundo, sendo responsável por perdas de solo superiores às taxas naturais de reposição. Objetivou-se estimar a distribuição espacial do potencial anual médio de perda de solo na bacia hidrográfica do Rio das Mortes (MG), com a finalidade de identificar as áreas mais susceptíveis à erosão hídrica e fornecer subsídio para a gestão dos recursos naturais na região. Para isso, foi aplicado o modelo RUSLE (Revised Universal Soil Loss Equation) implementado em ambiente SIG. O fator erosividade da chuva foi obtido com base em um modelo geográfico multivariado desenvolvido para o Brasil; o fator cobertura e manejo do solo foi derivado do mapa de uso do solo do Brasil; o fator erodibilidade do solo foi obtido pelo mapa de solos de Minas Gerais; e o fator topográfico foi obtido pelo modelo digital de elevação. Os mapas dos fatores foram combinados por meio de álgebra de mapas, originando o mapa de vulnerabilidade dos solos à erosão hídrica. Observou-se que 45,20% dos solos da bacia hidrográfica estudada apresentaram “Ligeira” vulnerabilidade à erosão hídrica. No entanto, 50,28% da área da bacia apresentaram perda de solo superior a 10 t ha-1 ano-1, o que indica a existência de áreas altamente susceptíveis à erosão hídrica e evidencia a necessidade de implementação de melhorias no manejo e práticas conservacionistas do solo.

scholarly journals Remote Sensing Analysis In RUSLE Erosion Estimation

2018 ◽  
Author(s):  
Ketut Wikantika
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Soil Loss ◽  
Spatial Information ◽  
Universal Soil Loss Equation ◽  
Large Area ◽  
Coverage Area ◽  
Erosion Processes ◽  
Long Time ◽  
Soil Loss Equation

Soil erosion is a major issue in various hemispheres. It is because erosion affects the survival of ecosystem. Diverse human actions, e.g., bushes burning and illegal logging, play a role in accelerating erosion. Climate factor such as rain intensity has also an influence in the release of soil particles. Therefore, a regular identification of those factors that affect erosion processes is highly needed in order to keep an environmental sustainable. Different areas in Indonesia have different erosion variable characteristics. One of the characteristics is indicated by the varieties ofvegetation cover, where a loose vegetation cover causes soil surfaces open for a long time period. Till now, researches dealing with the modeling of erosions with wide area coverage are few, since erosion observations have always been conducted by direct observations in the field, hence time consuming. Therefore, an erosion mapping model that is applied in a wide coverage area and the up to date of data is needed. Spatially, erosions can be depicted in a form of spatial information system model describing their potential class levels. There are several erosion models that can be used to find out the erosion occurring on a land, among others Universal Soil Loss Equation (USLE) model or its modification Revised Universal Soil Loss Equation (RUSLE). RUSLE erosion model consists of rainfall, soil erodibility, vegetation cover, slope gradient and length, and support practice factors. Recent technology in remote sensing allowed vegetation cover to beanalysed from satellite imagery, make the possibility of erosion analysis in large area in shorter time.

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 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 Minimização da erosão em função do tamanho e localização das áreas de floresta no contexto do programa "conservador das águas"

2011 ◽  
Vol 35 (6) ◽  
pp. 2157-2166 ◽  
Author(s):  
Cornélio Alberto Zolin ◽  
Marcos Vinícius Folegatti ◽  
Rafael Mingoti ◽  
Rodrigo Máximo Sánchez-Román ◽  
Janaina Paulino ◽  
...  
Keyword(s):  
Soil Loss ◽  
Minas Gerais ◽  
Universal Soil Loss Equation ◽  
Soil Loss Equation

Com os crescentes conflitos de uso da água no Brasil, a implantação de políticas para a mitigação desses problemas tornou-se crucial. Nesse sentido, o conceito de Pagamentos por Serviços Ambientais (PSA) tem se difundido ao redor do mundo e, consequentemente, no Brasil. O município de Extrema, em Minas Gerais, implantou a primeira iniciativa municipal brasileira de PSA, conhecida como programa "Conservador das Águas". Neste trabalho, objetivou-se avaliar a perda de solo na sub-bacia das Posses, onde se iniciou o programa "Conservador das Águas", visando determinar a potencialidade que o conceito adotado nesse programa terá para a conservação do solo e otimizar o provimento desse serviço ambiental em função do tamanho e da localização da área de floresta. Quatorze diferentes cenários de uso e cobertura do solo foram analisados, utilizando-se um Sistema de Informações Geográficas e a Revised Universal Soil Loss Equation. A expectativa de perda de solo na sub-bacia das Posses antes e após a implementação do programa "Conservador das Águas" foi de 30,63 e 7,06 Mg ha-1 ano-1, respectivamente. A otimização da conservação do solo pode ser feita adotando-se práticas conservacionistas na pastagem e alocando-se a área de floresta de maneira mais otimizada.

scholarly journals 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

2020 ◽  
Author(s):  
Veera Narayana Balabathina ◽  
Raju RP ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Lake Tana ◽  
Erosion Risk ◽  
Priority Areas ◽  
Erosion Rates ◽  
The Mean ◽  
Soil Loss Equation

Abstract Background: Soil erosion, one of the major environmental challenges, is influenced by topography, climate, soil characteristics, and human activities and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. The present study attempts to estimate soil erosion risk in the Northern catchment of Lake Tana basin, situated in northwest part of Ethiopia, with available data through the application of the Universal Soil Loss Equation model integrated with Geographic Information System and remote sensing technologies to identify priority areas for controlling soil erosion. In addition, it analyzes the effect of land use and land cover, topography, erodibility, and drainage density on soil erosion potential of the catchment, and the possible relationships among them. Results: The results show that the mean annual soil loss of catchment is estimated at 37.89 ± 59.2 t ha−1yr−1 with a total annual soil loss of 1,705,370 tons. The topography (LS-factor), followed by the support practice (P-factor) and the soil erodibility (K-factor) were the most sensitive factors affecting soil erosion in the catchment. To identify high priority areas for management, the study area was subdivided into five major sub-basins and further categorized into five erosion classes based on erosion severity. The mean soil erosion rates of the Derma, Megech, Gumara, Garno, and Gabi Kura River sub-basins are 46.8, 40.98, 30.95, 30.04, and 29.66 t ha−1yr−1, respectively. About 58.9% of the area was found in very low erosion risk which extends from 0-1 t ha−1yr−1 and accounted only 1.1% of total soil loss, while 12.4% of the area was found to be under high and extreme erosion risk with erosion rates of 10 t ha−1yr−1 or more that contributes about 82.1% of total soil loss warrant high priority for reducing the risk of soil erosion. Conclusions: This study permits the understanding of the soil erosion process and the various factors that lead to the spatial variability of the risk in the catchment, and thus enhances the effectiveness of proposed conservation strategies for sustainable land management.

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.

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