Cost-benefit analysis of local knowledge-based flood adaptation measures: A case study of Datian community in Zhejiang Province, China

Adaptation measures are important to deal with rising flood risk under a changing climate. Measures based on local knowledge (LK) is of great significance for communities to live with flood risks. However, the analysis on their costs and benefits is often overlooked. In this study, participatory GIS (PGIS) is used to explore LK in a flood-prone community in Zhejiang Province, China. By incorporating flood risk analysis, we apply the net present value (NPV) method to quantify the costs and benefits of LK-based flood adaptation measures (FAMs) (i.e., the wet-floodproofing, 0.5 m-uplift, 1.0 m-uplift and hybrid measures). Our results show that, the flood-prone community residents have gradually adopted FAMs through a series of flood experiences and learning processes. The LK-based FAMs can significantly reduce flood risk. With FAMs, the expected annual damage (EAD) decreases by 55.6-98.8%. All FAMs with three discount rates are feasible (NPV >0) regardless of short-, medium-, or long-term goals, of which the hybrid measure is the most desirable. Our work suggests that LK is beneficial in reducing flood risk and can be incorporated into decisions on resilient community building. Our approach can also be applied in other coastal communities for their cost-benefit analysis of LK-based FAMs.