Stormwater Symposium

Oral

394534 - A surrogate-based optimization framework for the deployment of low impact development solutions in large watersheds

Monday, June 4
2:00 PM - 3:30 PM
Location: Mirage Room
Co-Authors: Samira Fazlollahi, Singapore – Veolia City Modelling Centre; Stefano Galelli, Singapore – Singapore University of Technology and Design

Population growth, urbanization, and climate-driven changes in rainfall patterns have exposed cities to increasing flood risks. As a result, decentralized low impact development (LID) solutions are often combined with traditional centralized drainage systems to minimize flood risks during extreme rainfall events. The deployment of these solutions generally relies on a simulation-based optimization approach, which couples hydrological-hydraulic models with evolutionary algorithms or other metaheuristics. However, such approach has high computational requests—due to the complexity of the simulation models and the large number of iterations required by the evolutionary algorithms—which can prevent its application to large watersheds (or to a large number of rainfall events). To address this issue, we contribute a surrogate-based optimization framework: the key idea is to replace the high-fidelity hydrological-hydraulic simulation model with a simple, yet accurate, surrogate model characterized by limited computational requests. The framework is applied to a case study in the Nhieu Loc-Thi Nghe watershed, a 33-km2 area located in the central part of Ho Chi Minh City (Vietnam). We demonstrate that this framework is capable of providing significant computation time savings without compromising the quality of the solutions when compared to the optimization that uses the original simulation model (SWMM).

Jia Yi Ng

Singapore University of Technology and Design

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394534 - A surrogate-based optimization framework for the deployment of low impact development solutions in large watersheds



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