Runoff, Identification of Sensitive Zones in the Capivari Watershed – BA

• Autor(a) principal: Santana, Geisa Nascimento
• Data de Publicação: 2022
• Outros Autores: Silva, Luiz Artur Santos, Santos, Rosangela Leal, Delgado-Mendez, Jesus Manuel, Sampaio, Claudia Bloisi Vaz
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Sociedade & natureza (Online)
• Texto Completo: https://seer.ufu.br/index.php/sociedadenatureza/article/view/63971
• topic: Drainage basin; SCS-CN; Hydrology; Drainage basin; SCS-CN; Hydrology

The watershed is an active environment, defined as an area of land surface drained by a primary river and its tributaries, which are bounded by water dividers. Among the processes that affect water movement in a watershed, the surface runoff stands out, responsible for the transport of soil particles (nutrients and pollutants) to the lower parts of the landscape. The objective of this study was to demonstrate the influence of land use and cover on surface runoff dynamics in the Capivari Basin in Bahia, Brazil. To reach that objective, the Curve Number method (SCS-CN) was employed, with the ALOS/PALSAR RTC Digital Elevation Model; IBGE soil data; data from government weather stations and local agribusiness; land use and land cover from the LC08_L1TP_216069_20170619 landsat8 OLI sensor, through the classifier Bhattacharya. The processing was carried out on a GIS platform, using SPRING and QGIS software. Highest levels of precipitation, the soil features and the higher slope affected the greatest vulnerability to runoff at the mouth, based on the proposed model, however, the most conserved Permanent Preservation Area (PPA) have been effective in maintaining the Capivari River in these areas. The areas considered most critical in terms of the risk of water erosion for the year 2017 were those in the middle of Capivari, because they presented high precipitation in some months, but do not present PPA in riparian forest areas or in hill tops, this increases the vulnerability of these regions to erosion. The proposed model was successful in identifying areas most vulnerable to runoff in the Capivari Basin.