Aplicação qualitativa do modelo RUSLE na análise da susceptibilidade do solo à erosão com recurso aos sistemas de informação geográfica, caso de estudo: Distrito de Boane

Abstract

Erosion is a natural process of wear and tear on the Earth’s surface, intensified by human activities, such as inappropriate land use. Inappropriate anthropogenic land use compromises vegetation cover, reduces water infiltration and increases surface runoff, resulting in significant environmental impacts with repercussions for health, safety and social well-being. This study aims to assess the impact of erosion in the Boane District, Mozambique, based on the evolution and factors that influence soil susceptibility to erosion over a period between 2003 and 2023, considering the multi-temporal dynamics of 10 years of changes in land use and land cover. For this purpose, the Revised Universal Soil Loss Equation (RUSLE) was used, adapted to Geographic Information Systems (GIS), integrating data on rainfall erosivity (R), soil erodibility (K), topography (LS) and land use and management practices (CP), derived from satellite images obtained from the Landsat, Sentinel, SRTM programs and rainfall analyses obtained from the Climate Hazards Infrared Precipitation with Stations (CHIRPS) Group. The R factor was modeled using the Ordinary Kriging method, with a 20-year monthly rainfall history for each study. Meanwhile, the C factor was defined based on the supervised Maximum Likelihood classification, which assessed the variation in human intervention in land use and management practices. The topography was determined using map algebra techniques and GDAL and SAGA algorithms, and to determine the K factor, the soil type in Boane was related to the predefined erodibility table. Spatial regression techniques and the Moran Index were applied for robust analysis of the spatial autocorrelation of the data and to evaluate the explanatory capacity of the model through the coefficient of determination (R2). The R2 obtained for the years 2003, 2013 and 2023 was 0.972, 0.949 and 0.958, respectively, evidencing the strong influence of land use practices on susceptibility to erosion. The R2 results provide a scientific basis for monitoring and mitigating the impacts of erosion, providing technical-scientific support for sustainable land management(TRADUÇÃO NOSSA)