SIMULATION OF WATER QUALITY IN RIVERS BASED ON MACHINE LEARNING ALGORITHMS

Código

XXIV-SBRH0890

Autores

José Roberto Caseri, Angélica Nardo Caseri

Tema

SR05 - Hidrologia urbana e manejo de águas pluiviais

Resumo

Water is an essential resource for the population and for its development. Over the years, with the evolution of cities and with the development of industries, water quality has been degraded. Water quality monitoring systems are essential for water resources. Predictive models have an important role in the development of these systems, they enable the simulation of complex processes, such as the self-purification of rivers. This research verifies the capacity of machine learning models to predict Biological Oxygen Demand (BOD) of rivers. For this, historical data from the Tietê River in the city of São Paulo were used to develop the algorithms. The results obtained were satisfactory and could be an auxiliary solution in monitoring water quality.