Scenario-based flood risk assessment for urbanizing deltas using future land-use simulation (FLUS)

Abstract

Preparing cities for sea-level rise is one of the critical challenges of the twenty-first century. Extreme weather events, natural hazards, and the failure of climate mitigation and adaptation are substantial risks. These risks are especially significant in fast-urbanizing deltas, such as the Pearl River Delta in China, because the conflict between urbanization and flooding caused by climate change will be more significant in the future. This paper elaborates on an approach that employs a future land-use simulation (FLUS) model for scenario-based 100-year coastal flood risk assessment. Storylines of future scenarios from the Intergovernmental Panel on Climate Change (IPCC), called the representative concentration pathways (RCPs) 2.6 and 8.5, are utilized in the present study. The Guangzhou Metropolitan Area (GMA) is used as a case study to explore the probable implications of future land-use changes due to the ongoing urbanization process in the region in relation to projected environmental changes (sea-level rise, storm surge, and land subsidence). The results indicate that there will be a significant increase in flooded urban areas in the future. The simulations show that, as compared to 2015, the built-up area in the GMA will increase by 246.57 km² in 2030 and 513.03 km² in 2050. As compared to 2015, the flooding of built-up areas in 2030 and 2050 will respectively increase by about 31.32 km² and 48.49 km² under the RCP 8.5 scenario. It is also found that, as the main driving factor, urbanization will increase the flooding of built-up areas in Guangzhou in 2030 and 2050 by about 1.9 km² and 5.9 km², respectively, under the RCP 2.6 scenario as compared to 2015. Additionally, due to environmental changes, the flooding of built-up areas in Guangzhou will increase by about 24.2 km² and 26.8 km², respectively, under the RCP 8.5 scenario by 2030 and 2050 as compared to 2015. This increasing flood risk information determined by the simulation provides insight into the spatial distribution of future flood-prone urban areas to facilitate the development and prioritization of flood mitigation measures at the most critical locations in the region.