I-Corps: Automated water quality monitoring system using satellite data for measurements of water resource characteristics

The broader impact/commercial potential of this I-Corps project is the development of an online service to measure and report on lake water quality for government and business. Leveraging the ongoing investments for earth observation using satellites that provide free data, technology advancements like cloud computing and development of sophisticated algorithms, it is possible to automate the determination of water quality for every body of water in the world. Today, the methods and technology for monitoring lakes and field measurements are sparse with only on a small subset of lakes being monitored on a regular basis. Regulatory and policy entities could monitor water quality for every lake and reservoir on a regular basis with the capability of near real-time measurements to set policy and to better direct limited resources where they are needed most. The outcomes will be better management of a critical environmental resource for their constituents. Commercial entities such as vacation property businesses and real-estate brokerages will be able to better deliver value by reporting to consumers about the quality of lakes when renting, buying or selling properties. Lake water management companies would be able to continuously monitor the water quality to target treatment if needed. This I-Corps project is based on a software technology that processes remotely sensed satellite data into water quality products from all available Landsat 8 and Sentinel 2 imagery. Recent advances in satellite technology (improved spectral, spatial, radiometric and temporal resolution) and atmospheric correction, along with cloud and supercomputing capabilities have enabled the use of satellite data for automated regional scale measurements of water resource characteristics. Field-validated methods were developed and implemented in an automated water quality monitoring system on supercomputers. The system acquires satellite imagery, removes clouds, cloud shadows, haze, smoke, and land, and applies water quality models to deliver satellite-derived water quality products. Using these methods, a prototype database was created with monthly open water pixel level mosaics and lake level data for each clear image occurrence. The lake level (2017-2020) data includes 603,678 daily lake measurements of chlorophyll, clarity, and color (1,811,034 total) that were compiled into a database that was used to calculate water quality variables for different timeframes (e.g., monthly, summer (June-Sept)) and linked to a lake polygon layer that was used for geospatial analysis and included in a web map interface.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.