Diagnóstico de processos erosivos em solos agrícolas mediante análise de modelos numéricos do terreno

Abstract

Among the major problems related to environmental conservation in agricultural areas is soil degradation through water erosion, which causes the removal of the most fertile soil layers and the transport of soil particles to the lower parts of the relief, which contributes to the silting up of water resources. Therefore, the present study aimed to diagnose erosive processes in an area of agricultural production located at Fazenda Escola Capão da Onça - FESCON - UEPG, by analyzing data obtained by the Global Navigation Satellite System (GNSS) and Remotely Piloted Aircraft (RPA).For the accomplishment of the work a regular grid with points of 45 x 45 meters of distance was implanted, totaling 140 points in an area of approximately 26 hectares. Georeferencing of the regular grid points was carried out by means of post-processed GNSS signal receivers and the soil attributes collection (soil texture). The soil texture data collected in the regular grid provided the model for calculating the soil erodibility factor for the study area. With the altimetric values of the coordinates raised at the points of the regular grid it was possible to evaluate the vertical accuracy of Numerical Terrain Models generated through data obtained with RPA. The models generated with data obtained by means of fixed-wing and multirotor RPA equipment with the distribution of different numbers of control points and without control points were evaluated. by means of the statistical analysis applied in relation between the dispersion of the altimetric differences generated in the Numerical Terrain Model and the points of the regular grid used as reference, the Numerical Terrain Model generated with the fixed wing RPA data with control points presented the best result. In view of the finding of the best NTM, the topographic factor was modeled for the study area. The use of Geographic Information System GIS provided to integrate all the data in a unique computational environment; generate models through interpolation; analyze the accuracy of the models; implement the equations for the calculation of the erodibility and topographic factors and also the Revised Universal Soil Loss Equation (RUSLE); beyond the representations of the information. The result obtained with the model generated by RUSLE calculation showed that more than 70% of the study area is low susceptibility to erosion or slight soil loss. The rest of the study area presented soil loss above 10 ton / ha.year, indicating medium and high susceptibility to erosion.