Multi-scenario urban flood risk assessment by integrating future land use change models and hydrodynamic models

Urbanization and climate change are criticalchallenges in the 21st century. Flooding by extreme weather events andhuman activities can lead to catastrophic impacts in fast-urbanizing areas.However, high uncertainty in climate change and future urban growth limitthe ability of cities to adapt to flood risk. This study presents amulti-scenario risk assessment method that couples a future land usesimulation (FLUS) model and floodplain inundation model (LISFLOOD-FP) tosimulate and evaluate the impacts of future urban growth scenarios withflooding under climate change (two representative concentration pathways(RCP2.6 and RCP8.5)). By taking the coastal city of Shanghai as an example, wethen quantify the role of urban planning policies in future urbandevelopment to compare urban development under multiple policy scenarios(business as usual, growth as planned, growth as eco-constraints).Geospatial databases related to anthropogenic flood protection facilities,land subsidence and storm surge are developed and used as inputs to theLISFLOOD-FP model to estimate flood risk under various urbanization andclimate change scenarios. The results show that urban growth under the threescenario models manifests significant differences in expansion trajectories,influenced by key factors such as infrastructure development and policyconstraints. Comparing the urban inundation results for the RCP2.6 andRCP8.5 scenarios, the urban inundation area under the growth-as-eco-constraints scenario is less than that under the business-as-usualscenario but more than that under the growth-as-planned scenario. We alsofind that urbanization tends to expand more towards flood-prone areas underthe restriction of ecological environment protection. The increasing floodrisk information determined by model simulations helps us to understand thespatial distribution of future flood-prone urban areas and promote there-formulation of urban planning in high-risk locations.