Developing national-scale basic guideline on flood-adaptation strategies under climate change using probabilistic and deterministic factors.

As climate adaptation strategies against floods, implementing structural measures in damage-prone areas, supplemented by nonstructural measures (e.g., ecosystem-based disaster risk reduction (Eco-DRR)), is a viable approach. However, under climate change, predicting damage-prone areas is challenging, hindering the development of effective adaptation strategies. The increase in floods under climate change can be broadly attributed to probabilistic, triggerring hazards, and deterministic, inducing vulnerability factors. Therefore, quantification for levels of probabilistic and deterministic factors may establish adaptation strategies such as prioritize areas where structural measures should be implemented. Herein, we establish basic guideline for developing adaptation strategies against floods, considering probabilistic and deterministic factors simultaneously. We investigated all the municipalities in Japan and modeled flood occurrence from 2010 to 2019 based on government statistics, using the rainfall indicator as a probabilistic factors and terrain factor, which considers land use as a deterministic factor to decide appropriate indicators. Thereafter, we quantified the increase and decrease in rainfall indicator as probabilistic factor. Additionally, we used terrain factor, which considers current land use as a deterministic factor. We implemented nonhierarchical clustering using probabilistic and deterministic factors and classified 1795 municipalities in Japan into six clusters. The findings confirm the feasibility of developing specific adaptation strategies based on the clusters, such as strengthening the installation of artificial structures in areas belonging to the cluster in which floods expectedly increase and enhancing measures in clusters that remain unchanged based on flood histories.