Assessment of trade-offs among the co-benefits of nature-based solutions for flood risk reduction

The increasing uncertainty of urbanization and climate change has caused many urban problems to become increasingly prominent, especially those related to floods, which has prompted authorities and stakeholders to realize the importance of sustainable solutions. However, the traditionally grey drainage system is based on risk, which cannot adopt the uncertainty in the future. In theory, a large enough drainage system can solve any degree of flooding problems, but due to space constraints, it is less possible to blindly update and expand the capacity of the drainage system. In this respect, Nature-Based Solutions (NBS) has gradually become an alternative to grey infrastructure. NBS stands for a more ecosystem-friendly alternative that aims to enhance the natural water storage capacity by promoting the urban hydrological cycle processes. The proposed research aims to establish a framework to determine the co-benefits derived from NBS for flood reduction and evaluate the impact of NBS on these benefits. In addition, the optimal NBS strategy is established through cost-benefit analysis, but the optimal NBS strategy is not unique. Due to the different demands for various co-benefits and the different effects of NBS on co-benefits, it is necessary to identify the trade-offs among these co-benefits, thereby developing the most suitable NBS strategy for the study case. Based on the versatility of NBS, this research developed a method for optimizing NBS construction strategy. This method is based on questions regarding local characteristics and preferred benefits. Furthermore, the objective functions are formulated to maximize the primary benefit and co-benefits, as well as to minimize whole-life construction costs. Based on NSGA-II, this multi-objective optimization is used to obtain a series of optimal solutions, namely Pareto's front solution set. These optimal solutions are regarded as supports for reaching a compromise in the decision-making process. The calculation process and the call of NSGA-II are all completed in the python environment, while the one-dimensional hydrodynamics establishment and runoff and flooding rate are all simulated based on the SWMM 5.0 model and Pyswmm that is a Python extension package developed on EPA SWMM 5.0. This proposed methodology was applied to a case in Cul De Sac district, Sint Maarten Island. The four measures were screened, respectively green roof, permeable pavement, bio-retention pond, and open detention basin. There are four scenarios with the combination of several measures. Taking the maximum all benefits and flood reduction as respective optimization objects, all simulation results show that when all benefits are considered, the effect of the scenario with the four measures is better than other scenarios. However, when only flood reduction is considered, and the total cost is less than 40 million Euro, the scenario without green roof implementation gets the best result