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

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Abstract for “NSF Convergence Accelerator Track K: COMPASS: Comprehensive Prediction, Assess-ment, and Equitable Solutions for Storm-Induced Contamination of Freshwater Systems”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 resili-ency. 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 These disasters disproportionately affect un-derserved communities with outdated infrastructure and limited governmental resources.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 tem-poral 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, environmental justice, hydrologic modeling, distributed sensing, artificial intelli-gence, and quantum materials, seeks to empower communities to generate and implement equitable and sustainable solutions. The project's societal impacts extend to supporting policy decisions, incor-porating equity in adaptation solutions, and mitigating environmental impacts from flooding in vulner-able 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 I 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 envi-ronments. (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 I project establishes the groundwork for a potential Phase II initiative, aiming for an enhanced understanding of community vulnerability to storm-induced contaminants, advancements in scalable heterogeneous data acquisition for real-time flood and con-taminant 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.