Limitations of a Low-Cost Camera System for Monitoring Streamflow in an Extremely Small Forested Headwater Stream

Headwater stream dynamics are vital for understanding hydrological and ecological processes in watersheds; however, traditional monitoring methods can be costly and time-consuming. This technical note documents the limitations and challenges encountered when deploying a low-cost camera system for continuous streamflow monitoring in a forested headwater stream in Ohio, USA. The study stream, with a channel width of less than 1 m and watershed of 0.4 km2, is much smaller than previously studied streams. The camera system was constructed using inexpensive and easily accessible electronics, and it enabled application of large-scale particle image velocimetry (LSPIV) to videos collected at a frequency of 15 min. The application of LSPIV to much larger streams is well-established in previous studies; however, its application to extremely small headwater streams is understudied. Preliminary testing in a flume showed that this system was capable of providing accurate discharge measurements. In the field, however, a rating curve calibrated based on the LSPIV-derived flow estimates had an R2 value of 0.70, which was weaker than relationships previously reported in the literature. The rating curve overestimated flows at lower channel stages and underestimated them at higher stages when compared to physical discharge measurements. Examination of the videos collected during field deployment revealed that unsteady flow conditions introduced significant variability in the rating curve analysis. Environmental noise from raindrops, illumination conditions, and leaf litter also caused erroneous flow measurements in the LSPIV results. This technical note presents a critical evaluation of the performance of LSPIV-based camera system in extremely small streams, and practitioners and researchers are advised to follow several best practices, offered as lessons learned from our study, to minimize specific sources of error during implementation.