Spatiotemporal Effect of Land Use on Water Quality in a Peri-urban Watershed in a Brazilian Metropolitan Region: An Approach Considering GEP-Based Artificial Intelligence

Abstract

The suppression of natural spaces due to urban sprawl and increases in built and agricultural environments has affected water resource quality, especially in areas with high population densities. Considering the advances in the Brazilian environmental legal framework, the present study aimed to verify whether land use has still affected water quality through a case study of a peri-urban watershed in a Brazilian metropolitan region. Analyses of physical–chemical indicators, collected at several sample points with various land-use parameters at different seasons of the year, were carried out based on an approach combining variance analysis and genetic programming. As a result, some statistically significant spatiotemporal effects on water quality associated with the land use, such as urban areas and thermotolerant coliform (R = − 0.82, p < 0.01), mixed vegetation and dissolved oxygen (R = 0.80, p < 0.001), agriculture/pasture and biochemical oxygen demand (R = 0.40, p < 0.001), and sugarcane and turbidity (R = 0.65, p < 0.001), were verified. In turn, gene expression programming allowed for the computing of the importance of land-use typologies based on their capability to explain the variances of the water quality parameter. In conclusion, in spite of the advances in the Brazilian law, land use has still significantly affected water quality. Public policies and decisions are required to ensure effective compliance with legal guidelines.