Evaluating Performance of Individual and Combined LID Strategies for Urban Flood Reduction: An Integrated Modelling and Multi-Objective Optimization Approach

Urban flooding has increased in rapidly growing cities, indicating the necessity for sustainable stormwater management strategies. Low Impact Development (LID) strategies present potential solutions; however, assessing the collective effectiveness of various LID practices at the Indian watershed scale is complicated due to the complexity of spatial, hydraulic, and cost-related data. This study presents an integrated modeling and optimization strategy for implementing Green Roofs (GR), Rain Barrels (RB), and Permeable Pavements (PP) as Low Impact Development (LID) interventions to address urban flooding on the IIT Delhi Campus, a developing urban watershed in Delhi, India. A multi-objective optimization decision-support tool was developed by integrating the PCSWMM hydrological-hydrodynamic model with the NSGA-II evolutionary algorithm. This system aims to identify potential individual and combined LID allocation areas, taking into account both flood-reduction benefits and implementation costs. Simulations were conducted for return periods of 5, 10, 25, and 50 years to assess runoff volume, flood volume, and flood depth under ideal Low Impact Development scenarios. The findings indicate that the optimized LID strategies significantly decrease peak runoff and ponding depth. Among all LID solutions, GR demonstrated the lowest capacity for flood reduction, while RB and PP appeared to be more effective. Nevertheless, the combination of GR, RB, and PP outperformed each individual option. It was also observed that LID strategies demonstrate superior performance for lower return periods (5 and 10 years). However, performance decreases as rainfall intensity increases. The proposed framework offers significant insights into urban stormwater planning, illustrating how optimized LID allocation improves hydrological performance while reducing costs. This tool effectively aids hydrologists and urban planners in maximizing environmental and flood prevention benefits through the strategic selection and location of LIDs in rapidly urbanizing areas.

Keywords: LID, Optimization, Urban flooding