SEA for better climate adaptation in the face of the flood risk: Multi-scenario, strategic forecasting, nature-based solutions

Abstract

Numerous scholars have warned that many cities in the Greater Bay Area (GBA) are threatened by severe flood risk, which is often underestimated. Considering this, we provide a scenario-based Strategic Environmental Assessment (SEA) approach to analyse the roles of adaptation strategies on the environment in response to climate change and flooding risk. Three strategies are proposed including a non-Nature-based Solutions strategy (non-NbS), and two Nature-based Solutions strategies (NbS 1.0 and NbS 2.0). The non-NbS strategy refers to the way of promoting urban development yet no additional environmental concerns. The NbS 1.0 strategy focuses on ensuring arable lands for food security, and the NbS 2.0 strategy acquires further regulations on ecology protection.The analysis consists of two steps. First, this paper simulates the land use scenarios in 2030 and 2050, respectively, following non-NbS and NbS (1.0 & 2.0) strategies. This process is developed based on a patch-generating land use simulation (PLUS) model, which allows users to explore various future land use scenarios on account of different spatial development strategies, environmental conditions, and socio-economic trends. Second, the study overlays the land use scenarios with potential sea flooding scopes to reveal how different landscapes (e.g., forests and wetlands) are affected by carbon emissions in RCP 2.6 and RCP 8.5. Further research is suggested to incorporate the 2020 GDP data to refine the findings of this study and consider the impacts of dykes on flood-prone area mapping.The analysis finds that the NbS (1.0 & 2.0) strategies play an active role in decreasing the future flood risk of built-up areas in the GBA regionally, especially under the high-emission RCP 8.5 projection. However, their impacts vary between cities. (1) The NbS 2.0 strategy is effective in reducing the risk of built-up areas in Shenzhen, Hong Kong, and Macao, while the effectiveness of the NbS 1.0 strategy is not apparent. (2) The NbS 1.0 and 2.0 strategies are both effective in Dongguan, Guangzhou, Huizhou, Jiangmen, Zhuhai, Zhaoqing, and Zhongshan in reducing the flood risk of built-up areas. In addition, the NbS 2.0 strategy is more productive than the NbS 1.0 strategy either in 2030 or 2050. (3) The NbS 1.0 and 2.0 strategies generate subtle different effects in Foshan in 2030 and 2050. The NbS 2.0 strategy is more productive in 2050, while less productive in 2030. This study provides a comprehensive insight into the distributed flood risk following the non-NbS or NbS strategies in the context of climate change, which is useful to policymakers and urban planners.