Data Analysis and Water Quality Modeling in Urban Waterways

Project Summary

Research Advisor:  Zhenduo Zhu (Environmental Engineering)

Project Theme:  Pollutant Identification and Measurement

In urban waterways, it is especially important to estimate water quality under wet weather because of potential pollution from combined sewer overflows (CSOs), sanitary sewer overflows, and stormwater runoff. Quantification of all contaminant discharges is too challenging, and sampling and measurement of water quality parameters in urban waterways may be expensive and time-consuming. Therefore, it is very useful to analyze previous measurements and develop a predictive model based on historical data analysis. The objective of this project is to evaluate applicability of artificial neural networks in modeling water quality in urban waterways under wet weather conditions.

Primary Activities:  Data Analysis; Model Development

Skills/Courses Recommended:  Basic Knowledge of Fluid Mechanics; Introduction to Environmental Engineering; Enthusiasm for Data Analysis and Modeling

Anticipated Conference Participation:  ASCE-EWRI; Council on Undergraduate Research REU Symposium