Urban flooding occurs frequently in many regions of China. To reduce the losses caused by urban flooding, sponge city (SPC) and low-impact development (LID) have been carried out in many Chinese cities. However, urban flooding is influenced by various factors, such as climate, land cover characteristics and nearby river networks, so it is necessary to evaluate the effectiveness of LID measures. In this study, the Storm Water Management Model (SWMM) was adopted to simulate historical urban storm processes in the mountainous Fragrance Hills region of Beijing, China. Subsequently, numerical simulations were performed to evaluate how various LID measures (concave greenbelt, permeable pavement, bio-retention, vegetative swales, and comprehensive measures) influenced urban runoff reduction. The results showed that the LID measures are effective in controlling the surface runoff of the storm events with return periods shorter than five years, in particular, for one-year events. Furthermore, the effectiveness on traffic congestion mitigation of several LID measures (concave greenbelt, vegetative swales, and comprehensive measures) was evaluated. However, the effective return periods of storm events are shorter than two years if the effectiveness on traffic congestion relief is considered. In all evaluated aspects, comprehensive measures and concave greenbelts are the most effective, and vegetative swale is the least effective. This indicated that LID measures are less effective for removing ponding from most storm events in a mountainous, low-lying and backward pipeline infrastructure region with pressures from interval flooding and urban waterlogging. The engineering measures including water conservancy projects and pipeline infrastructure construction combined with the non-engineering measures were suggested to effectively control severe urban storms.

Green infrastructure (GI) is a contemporary area of research worldwide, with the implementation of the findings alleviating issues globally. As a supplement and alternative to gray infrastructure, GI has multiple integrated benefits. Multi-objective GI optimization seeks to provide maximum integrated benefits. The purpose of this review is to highlight the integrated multifunctional effectiveness of GI and to summarize its multi-objective optimization methodology. Here, the multifunctional effectiveness of GI in hydrology, energy, climate, environment, ecology, and humanities as well as their interrelationships are summarized. Then, the main components of GI multi-objective optimization including the spatial scale application, optimization objectives, decision variables, optimization methods and optimization procedure as well as their relationships and mathematical representation are examined. However, certain challenges still exist. There is no consensus on how to measure and optimize the integrated multi-functional effectiveness of GI. Future research directions such as enhancing integrated multi-objective assessment and optimization, improving life cycle analysis and life cycle cost, integrating benefits of GI based on future uncertainties and developing integrated green–gray infrastructure are discussed. This is vital for improving its integrated multifunctional effectiveness and the final decision-making of stakeholders.