Developing Data-Rich Video of Surface Water-Groundwater Interactions for Public Engagement

Communication of hydrologic data to the public can be improved by connecting data to the places they represent. In our example of data communication, we coupled hydrologic data with simultaneously collected video as both a scientific and public engagement tool. This note presents a method for collecting spatially and temporally dense datasets of water-quality and geophysical data on small streams and lakes, and for displaying the data in a user-friendly format using commercially available software. With this method, multiple instruments are mounted on a canoe and a controlled survey float is carried out to collect data. The data stream is georeferenced and logged using an Arduino microcontroller to provide detailed information about spatial variability. We employed these continuous data-collection methods at small streams and lakes across Wisconsin, USA. Comparison of stream-float sensor data to lab reported data, data collected by alternative sensors, and previously collected data in our study areas indicates that the low-cost temperature, electrical conductivity, pH, and dissolved oxygen sensors performed well. GoPro cameras recorded video throughout the duration of data collection. Our established water-quality and geophysical data collection methods are inexpensive, fast, and reliable, which qualify them as excellent tools for fine-scale spatial understanding of stream and lake habitats' health. Data-rich video connects point measurements of water properties to the appearance of the native environment. This method helps improve our understanding of groundwater and surface water interactions in complex hydrogeologic systems, enhance communication amongst stakeholders, and provide context when monitoring and managing sensitive habitats.

Automated summary

This article presents a method for improving the communication of hydrologic data to the public by connecting data to video representations. The authors collected water-quality and geophysical data using multiple instruments mounted on a canoe and recorded video using GoPro cameras. The data was georeferenced and logged using an Arduino microcontroller. The results show that the low-cost sensors performed well and the data-rich video provided context for the measurements. This method enhances spatial understanding of hydrogeologic systems and facilitates communication and management of sensitive habitats.