The Role of Emerging Technologies in Monitoring Groundwater-Soil Systems

Abstract:

Groundwater is central to the water-food-energy nexus. Unfortunately, we have been slow to recognize the impacts of the industrial revolution of the 20th century on groundwater. The contaminated sites in our living spaces can take decades and 100s of millions of dollars to clean up. The current methods for monitoring existing contaminated sites are antiquated, commonly ineffective, and expensive. And even now, there is no rapid and economical way to detect new unintended leaks of chemical into groundwater. Advances in sensor technology, edge computing, IoT, big data, machine learning, and AI are exactly what is needed to address this issue.

Our solution is to employ large numbers of durable low-cost sensors to characterize/monitor contaminated water, soils, and sediment. Primary sensors parameters include soil redox (oxidation reduction potential), temperature, and water levels. Sensor data are supplemented by local meteorology/hydrology data. Synergistically, the data streams are applicable to environmental monitoring of water, soils, and sediments, in natural settings and in active treatment systems. Large multiple-parameter data sets will be automatically uploaded to cloud-based data storage, and AI will be used to transform data into real-time actionable output. Combined sensor-based big data and AI will lead to a cleaner environment, reduced environmental monitoring costs, greater safety for workers, increased security at critical facilities, and a reduced carbon footprint for environmental monitoring.