Municipal Separate Storm Sewer System (MS4) compliance has become increasingly complex and financially demanding due to expanding environmental regulations, watershed protection mandates, and urbanization-driven increases in stormwater runoff. Municipalities are required to achieve measurable pollutant reduction targets while managing constrained public budgets, creating a critical need for cost-efficient compliance strategies. This study develops a cost-efficiency modeling framework that integrates environmental performance evaluation with economic optimization to assess how municipalities can minimize compliance expenditures while maintaining regulatory effectiveness. The research applies lifecycle cost analysis, constrained optimization modeling, and performance-based evaluation to examine relationships among infrastructure investment, monitoring intensity, and regulatory outcomes. Results indicate that compliance costs are primarily driven by capital infrastructure upgrades, monitoring requirements, and maintenance obligations, while reactive planning approaches significantly increase long-term expenditures.
Optimization simulations demonstrate that integrated financial engineering decision models improve compliance performance and reduce lifecycle costs through strategic investment allocation and phased infrastructure implementation. Findings further reveal that balanced deployment of gray and green infrastructure solutions yields higher cost efficiency compared with single-approach investment strategies. The study highlights the importance of proactive planning, data-driven monitoring, and lifecycle budgeting in achieving sustainable MS4 compliance. Policy implications suggest that performance-oriented regulatory frameworks and flexible compliance mechanisms can support municipal innovation while maintaining environmental accountability. Overall, the proposed framework provides a structured analytical foundation for aligning environmental governance objectives with municipal fiscal sustainability, contributing to improved decision-making in urban stormwater management systems.