NSF Convergence Accelerator Track K: COMPASS: Comprehensive Prediction, Assessment, and Equitable Solutions for Storm-Induced Contamination of Freshwater Systems

University Of South Carolina At Columbia, Columbia SC

Investigators

Abstract

The project addresses the challenges of freshwater quality and quantity by integrating next-generation sensors, advanced flood modeling, and co-generated policy knowledge to enhance community resiliency. Extreme weather events often result in the release of toxic chemicals, raw and partially treated sewage, and agricultural wastes into the environment. These disasters disproportionately affect American communities with outdated infrastructure and limited governmental resources. Focused on the Pearl River Watershed in Mississippi and the Santee River Basin in South Carolina, the research employs a modular sensor system, including unpiloted aerial vehicles and low-cost Nuclear Magnetic Resonance (NMR) spectrometers, to assess contaminant dispersion in watersheds. Through a data-driven and physics-based modeling approach, the project aims to provide reliable spatial and temporal projections for water quality and quantity, supporting decision-makers in monitoring freshwater systems and planning for water emergencies. The interdisciplinary team, combining expertise in social sciences, public policy, hydrologic modeling, distributed sensing, artificial intelligence, and quantum materials, seeks to empower communities to generate and implement sustainable solutions. The project's societal impacts extend to supporting policy decisions, incorporating adaptation solutions, and mitigating environmental impacts from flooding in American communities. The project focuses on developing low-cost, field-deployable NMR sensor systems, integrating data collection methods with hydrologic modeling, and adopting a system of socio-environmental systems approach. This integrated approach is required to overcome challenges in real-time data collection and the transition of academic research into actionable solutions. Low-cost and easy-to-deploy in situ NMR provides optimal sensing technology for developing a contaminant detection, quantification, and tracking system without constraining sensor development to focus on a specific contaminant. Key components of the project’s Phase 1 scope of work include: (a) Refining an open-source compact NMR sensing system developed by the research team for in-situ monitoring of contaminants in aquatic environments. (b) Developing a coupled flood and contaminant modeling and monitoring framework to predict and respond to flooding and flood-borne contaminants with enhanced accuracy and timing. (c) Modeling the complexities and feedback loops inherent in integrated socio-environmental systems using a system of systems approach. The Phase 1 project establishes the groundwork for a potential Phase 2 initiative, aiming for an enhanced understanding of community vulnerability to storm-induced contaminants, advancements in scalable heterogeneous data acquisition for real-time flood and contaminant tracking, and equipping communities with tools to design adaptive, active, and sustainable next-generation infrastructure. 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.