Date of Graduation

5-2026

Document Type

Thesis

Degree Name

Bachelor of Science in Industrial Engineering and Operations Analytics

Degree Level

Undergraduate

Department

Industrial Engineering

Advisor/Mentor

Curry, Rob

Committee Member

Sullivan, Kelly

Abstract

Due to limited technical and financial resources, urbanizing rural communities often face growing stormwater management challenges while undergoing rapid development. This thesis proposes a mixed-integer linear programming (MILP) framework that integrates topography-driven stormwater flow behavior, infrastructure placement constraints, and multiple planning objectives to support cost-effective stormwater infrastructure decisions. Our model accounts for budget constraints, gravity-driven surface water flow, infiltration capacity, and spatial contiguity requirements to determine optimal pond placements that balance flood reduction and implementation costs. A synthetic discretized grid representing a small municipality is used to demonstrate model behavior under varying rainfall and topographic conditions. Results demonstrate the framework's ability to expose important planning trade-offs: topographic configuration significantly influences infrastructure costs and optimal placement patterns, while stakeholder prioritization of budget constraints versus flood mitigation objectives yields distinct spatial strategies, enabling systematic exploration of how physical factors and community preferences interact to shape feasible alternatives. Together, these findings demonstrate how the proposed approach can help planners systematically evaluate trade-offs between physical constraints and stakeholder input, supporting transparent trade-off analysis in resource-constrained environments.

Keywords

Stormwater; Optimization; Prairie Grove; Rural

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