Multiscale Hydrogeologic-Biogeochemical Process Monitoring and Prediction Framework

Remediation and long term management of contaminated sites is likely to require hundreds of billions of dollars. Most of the sites which remain in the US inventory of contaminated sites do not have simple solutions, and effective remediation of these sites will require a fundamental, timely and actionable understanding of physical, chemical and biological processes and overall system behavior in complex subsurface environments. A cloud based predictive assimilation framework (PAF) is being developed which will provide timely and actionable information on current and future subsurface site behavior to stakeholders. This software is being constructed such that it will be broadly applicable to a range of contaminated sites and subsurface problems. The framework ingests, manages and assesses observational data from multiple sources and processes this data using inversion and prediction methods to then deliver data and information to stakeholders in a timely manner. In Phase I an operational prototype of this framework was constructed and successfully demonstrated on a highly instrumented contaminated site. In Phase II we will expand the data processing and parameter estimation capabilities of this framework as well as the underlying software architecture. Commercial Applications and Other Benefits: The framework will provide a predictive understanding of the behavior of contaminated sites. The framework will also be applicable to aquifers, sites used for CO2 sequestration and sites where environmental surveillance is required. The framework will provide a low cost solution to environmental characterization and monitoring.