Behavior simulation of nitrogen compounds in rivers with uncertainty analysis

• Autor(a) principal: Fortunato,Tatiana Candeia da Silva
• Data de Publicação: 2020
• Outros Autores: Reis,José Antonio Tosta dos, Mendonça,Antonio Sérgio, Silva,Fernando das Graças Braga da
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Ambiente & Água
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-993X2020000300313
• topic: monte carlo method; stochastic modeling; uncertainty analysis; water quality

Abstract This study simulated nitrogen-compound concentration changes in rivers, taking into account uncertainty analysis carried out by the Monte Carlo Method. The study area is the final stretch of the Piracicaba River, located in Minas Gerais, Brazil, which is an important Doce River tributary. The uncertainty analysis took into account random generation of hydrodynamic variables, initial water quality conditions and kinetic constants. Different variation percentages for the organic nitrogen decay kinetic constants random generation did not influence considerably the ammonia or organic nitrogen maximum concentration extreme values. In the simulations, maximum organic nitrogen concentrations were most frequently between 0.20 mg.L-1 and 0.22 mg.L-1 (42%), maximum ammonia nitrogen between 0.28 mg.L-1 and 0.30 mg.L-1 (30%), maximum nitrite between 0.05 mg.L-1 and 0.07 mg.L-1 (49%) and maximum nitrate between 0.46 mg.L-1 and 0.50 mg.L-1 (37%). Estimated maximum concentrations for ammonia nitrogen, nitrite and nitrate did not exceed the environmental quality standards established by Brazilian CONAMA Resolution 357/2005 for Class 2 watercourses. Random generation of kinetic constants that regulate ammonia and nitrite decay produced significant ammonia nitrogen, nitrite, and nitrate peak concentrations value frequencies, histograms and forms changes, when considering variation percentages equal to or greater than 50%. Some simulation results showed more inhibition of oxidized nitrogen forms production.