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Modeling Platform as an Innovation Playground for Advances in Characterization and Remediation of Contaminated Sites
  • Parisa Jourabchi
Parisa Jourabchi
ARIS Environmental Ltd.

Corresponding Author:parisa@arisenv.ca

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Abstract

The importance of water supplies cannot be overstated, yet contaminant monitoring and management have not seen strong innovation in information and computing technologies (ICT) such as internet-of-things (IoT), big data, arti>cial intelligence (AI) and numerical modelling. As a water risk, regulated contaminated sites are unique in that they have owners with obligation and cost responsibility, creating conditions that traditionally drive technology innovation. As contaminated site management moves toward risk management rather than resource intensive remediation, ICT technologies will be increasingly applied. A high subsurface complexity, varying land and local weather conditions, however, strongly impact contaminant fate and transport to make each site unique. Site uniqueness means that development of innovation is slow to occur due to lack of scale economic bene>ts. For this reason, a key technology suited for early adoption is reactive transport modeling (RTM). Such modelling can be coupled with diverse compute technologies (e.g. Steefel et al. 2021) supporting long term site modeling for climate change. In this presentation, we explore a modeling platform for data-driven RTM. The work draws from extensive research efforts on quantitative, process-based approaches and measurement methods that span multiple disciplines (e.g. Sookhak Lari et al. 2019). Challenges and limitations of such an RTM platform are discussed, considering: 1) complexity levels, modularity, and computational requirements; 2) existing models; 3) adaptiveness to sitespeci> c data and predictive analytics; 4) upscaling of pore-scale processes; 5) platform Rexibility to account for natural depletion processes (e.g. variably saturated media; microbial dynamics; heat transport; contaminant distribution); 6) platform and model operations to handle in situ remedial activities (e.g. point injections; surface cover / solarization; phytoremediation); 7) use of intelligent systems to provide select model parameters from existing big data sets. An RTM platform is an innovation that has many bene>ts, providing a ‘digital twin’ for contaminated site decision making and an ‘innovation playground’ for novel characterization and remediation techniques.