Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado

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• 作者：Elias Rodrigues da Cunha ; Vitor Matheus Bacani ; Elói Panachuki
• 关键词：Erosion ; Soil conservation ; RUSLE ; GIS ; Pantanal
• 刊名：Natural Hazards
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：85
• 期：2
• 页码：851-868
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Natural Hazards; Hydrogeology; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Civil Engineering; Environmental Management;
• 出版者：Springer Netherlands
• ISSN：1573-0840
• 卷排序：85

文摘

The installation of a rural settlement complex in the watershed stream Indaiá has promoted changes in land-use and vegetation cover dynamics; however, the effects of intensive agriculture and cattle farming in rural settlements on soil loss rates are not well known. Predictive models implemented in geographic information systems have proven to be effective tools for estimating erosive processes. The erosion predictive model Revised Universal Soil Loss Equation (RUSLE) is a useful tool for analyzing, establishing and managing soil erosion. RUSLE has been widely used to estimate annual averages of soil loss, by both interrill and rill erosion, worldwide. Therefore, the aim of this work was to estimate the soil loss in the watershed stream Indaiá, using the RUSLE model and geoprocessing techniques. To estimate soil loss, the following factors were spatialized: erosivity (R), erodibility (K), topography (LS), land-use and management (C) and conservation practices (P); the annual soil loss values were calculated using the RUSLE model equation. The estimated value of soil loss in the hydrographic basin ranged from 0 to 4082.16 Mg ha−1 year−1 and had an average value of 47.81 Mg ha−1 year−1. These results have demonstrated that 68.16 % of the study area showed little or no soil loss based on the Food and Agriculture Organization’s (FAO 1980) classification. When comparing the average value of soil loss obtained using the RUSLE model with the Natural Potential for Erosion, a 16-fold reduction in soil was found, which highlighted the fact that vegetation cover (C factor) has a greater influence than other factors (R, K and LS) on soil loss prediction attenuation. These results lead to the conclusion that soil loss occurs by different methods in each settlement in the basin and that erosive processes modeled by geoprocessing have the potential to contribute to an orderly land management process.