SBIR Phase II: Envimetric - Soil and water contamination predictive modeling tools

The broader impact/commercial potential of this Small Business Innovative Research (SBIR) Phase II project is a significant reduction in the cost and time to remove hazardous contaminants from the soils and groundwater impacting communities. Properties observed from thousands of contaminated sites serve as inputs to a computerized mathematical model of the site, forecasting the most likely shape and depth of a contaminant plume. This machine learning model gives remediation planners access to a fast delineation of volume to be remediated as well as the uncertainty of the modeled estimate. This saves time and money searching for these contaminants that are deep underground and in groundwater. This Phase II project will expand on the Phase I prototype, creating an operational product capable of reaching the needs of environmental engineers and scientists around the globe, providing the stimulus to cut remediation time and cost in half. 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.