Optimization of Regional Stormwater Quality Control Systems Using Genetic Algorithms

Stormwater system management with a set of objectives in urban watersheds is often achieved by effective design and use of detention ponds. These ponds help mitigate impacts of urban drainage from water quantity and quality perspectives. The design, site selection for these ponds, operation and management over time are important aspects of effective stormwater management. This involves costs to land developers and there is always a need for minimizing these costs at that same time fulfilling the objectives of the management with environmental and regulatory compliance. A nonlinear programming formulation and genetic algorithm (GA) based optimization approaches are proposed to design a single stormwater detention pond system in the current study. The optimization methodology is also extended to consider multiple detention systems. The main objective is to minimize the cost constrained on system performance related to pollution control. The optimization techniques employs analytical probabilistic models for urban stormwater management analysis which mathematically closed form are enabling them easily integrated into optimization frame work. The results provide optimal design parameters considering the runoff control and pollutant reduction considering environmental and regulatory issues. Application of the methodology for a case study system is demonstrated with results and the benefits of using GA based optimization approach are illustrated.