Predicting soil erosion using Rusle and NDVI time series from TM Landsat 5

Abstract

-The objective of this work was to evaluate the seasonal variation of soil cover and rainfall erosivity, and their influences on the revised universal soil loss equation (Rusle), in order to estimate watershed soil losses in a temporal scale. Twenty-two TM Landsat 5 images from 1986 to 2009 were used to estimate soil use and management factor (C factor). A corresponding rainfall erosivity factor (R factor) was considered for each image, and the other factors were obtained using the standard Rusle method. Estimated soil losses were grouped into classes and ranged from 0. , respectively. Mean annual soil loss in the watershed was 109.5 Mg ha -1 , but the central area, with a loss of nearly 300.0 Mg ha -1 , was characterized as a site of high water-erosion risk. The use of C factor obtained from remote sensing data, associated to corresponding R factor, was fundamental to evaluate the soil erosion estimated by the Rusle in different seasons, unlike of other studies which keep these factors constant throughout time.Index terms: C factor, rainfall erosivity, remote sensing, soil loss, vegetation index. Predição da erosão do solo com uso da Rusle e séries temporais de NDVI do Landsat 5 TMResumo -O objetivo deste trabalho foi avaliar a variação estacional da cobertura do solo e da erosividade da chuva e suas influências na equação universal de perda de solo revisada (Rusle), para estimar as perdas de solo em uma microbacia, em escala temporal. , mas a área central da bacia, com perdas de aproximadamente 300,0 Mg ha -1 , foi considerada como de alto risco à erosão pela água. O uso do fator C obtido a partir da técnica de sensoriamento remoto, associado ao fator R correspondente, é fundamental para avaliar as perdas de solo estimadas pela Rusle em diferentes épocas do ano, diferentemente de outros estudos em que estes fatores são mantidos constantes ao longo do tempo.Termos para indexação: fator C, erosividade, sensoriamento remoto, perda de solo, índice de vegetação.

Spatial Modeling of Soil Erosion Risk and Its Implication for Conservation Planning: the Case of the Gobele Watershed, East Hararghe Zone, Ethiopia

“…It is also higher than the findings of earlier researchers in other areas in Ethiopia [27,33,127], and elsewhere in the world [128,129]. On the contrary, the present study results are lower than the findings across the Northwestern Ethiopia highland [130], and other similar studies' findings [131][132][133]. Several previous studies suggested that vulnerability to a higher rate of water-induced soil erosion occurring in eastern Ethiopia's highland is associated with the adverse effects of LULC changes, an unsustainable land management, and less emphasis is given to SWC practices [7,134,135].…”

Soil physical properties and soil organic carbon content in northeast Brazil: long-term tillage systems effects

“…Soil physical degradation involves reduction of soil structure, leading to soil compaction, wind and water erosion and soil organic carbon (SOC) mineralization. Although certain classes of soil are more prone to degradation, for instance, Inceptisols and Ultisols (Carvalho et al, 2014), soil mismanagement and land misuse, i.e. indiscriminate plowing and negative SOC budgets may exacerbate soil quality decline (Lal, 2015).…”

Soil erosion risk zoning in the Ecuadorian coastal region using geo-technological tools

“…So the qualification and quantification of soil erosion, is important as regards, assessing land units because it has effects such as the loss of the nutrients required for crop growth, the accumulation of sediments in river channels, and a reduction in water storage capacity owing to soil loss, thus reducing the natural flow of catchments (Fonseca et al, 2014).…”