Avaliação da qualidade da água de chuva e de um sistema filtro-vala-trincheira de infiltração no tratamento do escoamento superficial direto predial em escala real em São Carlos - SP

Abstract

Several studies cite the pollution of stormwater as equivalent and sometimes even superior to those found in the sewers. According to this premise and thinking about environmental issues, especially in the contamination of groundwater and the spread of waterborne diseases, the quality of rainwater has become an important focus of study. This work concerns the monitoring of an infiltration system consisting of grass filter, trench and infiltration trench, built in full scale on the campus of University Federal of São Carlos - UFSCar, located in São Carlos - SP, from the assessment water quality of runoff directly before and after passing through the proposed infiltration system, parallel to monitoring the quality of rain water, through analysis of the physico-chemical and bacteriological established in legislation and international experiences, compared the conditions of the study area, and exploratory data analysis by two chemometric techniques: Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA). According to the analysis of the results variation, especially the quality of atmospheric water and quality of direct runoff results were obtained as concentrations low significantly to parameters Turbidity, Color, ST, STD, Nitrate, Nitrite, Ammonia nitrogen, Sulfate, Chloride, Cadmium, Copper, Lead and Zinc in the water samples analyzed directly from rain, compared with previous studies in the literature and standards and legislation existing about water resources, and the efficiency of the infiltration trench in the removal of Zinc (90,89%), Cooper (88,31%), Electrical Conductivity (31,40%), Ammonial nitrogen (24,32%) and Chloride (5,88%) compared with the predial direct runnof in the channel. With regard to PCA analysis, proves the characteristics between samples according to the conditions of sampling (day, month, place and time) and analysed variables, dividing into groups of samples and contributing to the extraction and interpretation of information unlikely to be viewed directly in the data matrix. The analysis complemented by HCA analysis by PCA.