Dynamic flood adaptation pathways for Shanghai under deep uncertainty
Xinmeng Shan, Jeroen C. J. H. Aerts, Jun Wang, Jie Yin, Ning Lin, Nigel Wright, Mengya Li, Yuhan Yang, Jiahong Wen, Fengyue Qiu, Paolo Scussolini
Abstract
Decision-making for flood adaptation in coastal cities is complicated by deep uncertainty about sea level rise, subsidence, and socioeconomic trends, which increases the possibility of under- or over-investment. Using the megacity of Shanghai as a case study, we apply the dynamic adaptive policy pathways (DAPP) framework to demonstrate robust and flexible decision-making under uncertainty. The framework integrates compound flood risk modeling of flood risk, economic evaluation, and dynamic adaptation pathways. Our results show that without adaptation, annual damages and annual casualties could increase by 86–167%, and 45–97 times, respectively, by the year 2100. ‘Hard adaptation strategies’ such as levees can reduce projected damages by 58–94%. In contrast, local scale ‘soft adaptation’ (flood-proofing buildings) is only effective and economically efficient in combination with hard adaptation (‘hybrid strategy’). The best economic performance is a hybrid strategy that starts implementing a large storage tank adding a mix of measures around 2050 (coastal wetlands, dry-floodproofing, and land elevation). Depending on how the future plays out, a hybrid strategy of a combination of a storm-surge barrier and coastal wetlands would yield high economic benefits after ~2070.