Evaluating and Monitoring BMPs with Networked Wireless Sensors

Abstract

Minnehaha Creek and the Mississippi River, like most other bodies of water, have contaminants flowing in them during all times of the year. These contaminants impact the environment differently depending on their nature; some are less harmful than others even though they might have a higher concentration in the water. Turbidity and high chloride concentrations are two indicators that a body of water is impaired, either for human use or ecologically. Best Management Practices, or BMPs, can help diminish these contaminants in many ways, such as settling small particles (turbidity) out of the water. I have been analyzing data collected from in-situ wireless sensors, comparing data upstream from various BMPs to downstream, and also analyzing the data to determine if water quality standards are violated. Stormwater outfalls into the Mississippi were monitored and compared with standards as well, in order to observe if these outfalls increased the concentrations of pollutants, particularly chloride or the turbidity, in the river over time. By determining the BMP performance, water quality around the metro can be monitored more accurately and the quality of its surface water will be secure into the future.