Author ORCID Identifier

https://orcid.org/0009-0000-1287-9997

Semester

Spring

Date of Graduation

2026

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Civil and Environmental Engineering

Committee Chair

Kevin Orner

Committee Member

Lian-Shin Lin

Committee Member

Emily Garner

Committee Member

Leslie Hopkinson

Committee Member

Pablo Cornejo

Abstract

Lagoon wastewater treatment systems are among the most widely used secondary treatment technologies serving small and rural communities in the United States due to their low capital and operating costs, minimal energy requirements, and operational simplicity. While effective for removal of organic matter and suspended solids, most lagoon systems were not designed to achieve advanced nutrient removal. As regulatory priorities increasingly emphasize control of total nitrogen and total phosphorus to protect receiving waters and public health, lagoon-dependent communities face growing compliance challenges. These challenges are exacerbated by aging infrastructure, limited technical capacity, financial constraints, and insufficient infrastructure data, highlighting the need for lagoon-specific, context-appropriate nutrient management strategies.

The overarching goal of this research was to generate accessible technical, environmental, economic, and spatial information to support the selection of cost-effective and sustainable nutrient management strategies for lagoon systems in the U.S. serving populations under 10,000. This was achieved through five interrelated components. First, a comprehensive systematic review of over 1,000 peer-reviewed studies identified and classified nutrient removal technologies applicable to lagoon systems, resulting in the development of a lagoon-specific Suitability Index to assess feasibility under small-community constraints. Second, a national-scale assessment of lagoon nutrient management infrastructure characterized lagoon configurations, nutrient permitting practices, and performance variability, revealing persistent regulatory and data gaps that hinder performance benchmarking and informed planning. Third, a GIS-based deep learning framework was developed to identify and characterize lagoon systems using aerial imagery, improving infrastructure visibility in regions lacking detailed records. Fourth, integrated life cycle assessment and life cycle cost analysis quantified the environmental and economic trade-offs of representative lagoon nutrient management strategies, demonstrating that targeted upgrades substantially reduce eutrophication impacts at increased cost. Lastly, the life cycle assessment findings were synthesized within a multi-criteria decision support framework that incorporated environmental, economic, social, and technical indicators to enable transparent comparison of nutrient management alternatives.

Together, the findings demonstrate that while no single nutrient management strategy is universally optimal, context-specific decision-making can significantly improve nutrient removal performance while balancing affordability, operational feasibility, and environmental outcomes. By addressing long-standing data gaps and aligning technical analysis with the realities of small-community lagoon systems, this research provides an integrated framework to support more equitable, transparent, and sustainable nutrient management decisions.

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