Estudo sobre a aplicação do modelo SWAT através do complemento QSWAT+ nos arroios Cambai e Olarias em Itaqui - RS

Abstract

Taking into account the advancement of geotechnology and its growing accessibility, we can say that geoprocessing-based tools have stood out for their efficiency in gathering territorial data, as these technologies are widely used for analyses such as land use and occupation, hydrological modeling, among others, allowing detailed studies of soils, vegetation and water resources. An example of this is the Soil & Water Assessment Tool (SWAT), which has revolutionized environmental analysis, offering graphic representations and maps that illustrate the impact of human activities on water, soil and vegetation. By using these tools in the municipality of Itaqui/RS, especially in the Cambaí and Olaria stream basins, it will be possible to gain a better understanding of the region. Therefore, this work aimed to identify steps for preparing input data for the SWAT model, requested by the QSWAT+ add-on within the QGIS geographic information system software. Also, through the delimitation of the area where the Cambaí and Olaria streams meet in QSWAT+, to visualize land use and land cover in the region under study. The delineation of sub-basins and the analysis of land use and cover revealed problems such as anthropogenic impact in urban and agricultural areas. This study, together with the LABii project - Integrated Interdisciplinary Laboratory, linked to UNIPAMPA - Campus Itaqui, stands out for integrating hydrological modeling with academic practices, with students and researchers building maps and analyzing the model, strengthening the practical application of geotechnologies in the educational environment. The conclusion is that there was an important analysis of the model and its necessary inputs for using the model, thus enabling the process to be applied later by researchers interested in the subject, this mainly focused on the area under study in the region of the municipality of Itaqui. In addition, the effort made in this work will be used in the future by the LABii team to continue this study in 2025.