摘要: |
Robust and reliable information is needed regarding stormwater infrastructure performance to effectively manage pollutants from stormwater runoff. In particular, measuring outlet flow magnitudes is important as outlets provide the critical function of regulating flow for structural stormwater control measures (SCMs), thus outlet monitoring aids in evaluating performance and identifying possible design problems and causes for failure. The current state of practice is to use sensors or other instrumentation for monitoring flow; however, these systems can be expensive, require multiple components, and are placed in harsh environments, which decreases their expected lifetime. Modeling approaches may be used instead to predict flow; however, model accuracy relies on rainfall estimates and information regarding SCM conditions, which may not always be available or accurate. Therefore, there is a need to develop methods for low-cost, quick-deployment, extended-term outlet monitoring such that timely action can be taken when problems first occur, to evaluate performance during significant precipitation events, and to have a better understanding of system performance over time. To address this need, this project aims to implement and validate a long-term, low-cost, and accurate computer vision-based technology to monitor pipe outlet flow in the field. |