The dynamic of seasonal nonpoint pollution in complex watersheds.

• Ano de defesa: 2022
• Autor(a) principal: Magalhães, Ariel Ali Bento
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Best management practices; Melhores práticas de gestão; Modelagem matemática; Modelling; Nonpoint pollution; Poluição difusa; Qualidade da água
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/3/3147/tde-22052023-084020/

Periods of drought are impactful in terms of surface water quality, as there is less mass available to dilute the released contaminants. However, it has now been determined that the cause of substantial effects on water and aquatic habitat is surface runoff caused by rainfall-flow process. Although not receiving as much attention, diffuse pollution (runoff, deforestation, fertilizers from farmland, etc.) is just as harmful as point pollution (from treatment plants, industrial discharges, etc.). Thus, the coupling of hydrological, load and hydrodynamic models related to water quality is becoming increasingly important. The development of the CABC-QUAL model in this work was thought to help with these complex issues, which include the multiples uses of the watershed and the variability of precipitation itself, the different forms of sanitary systems and the seasonality of the constituents. In addition, a tool was included to manage Best Management Practices (BMP) through in situ Treatment Units, which proved to be a great helper for positioning these practices to reduce pollution in surface waters. In the two case studies used to validate the developed model, the CABC-QUAL demonstrated its ability to perform all its tasks accurately, quickly and completely. It also demonstrated results on an annual time scale, discussing all the complexity of the variation in constituent concentrations distributed across the basin. This tool will be essential to represent the complexity of water quality more accurately and will serve as support for depollution programs.