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

Area of Science:

• Environmental Science
• Climate Change Adaptation
• Disaster Risk Reduction

Background:

• Climate change exacerbates flood risks, complicating the identification of vulnerable areas for effective adaptation.
• Flood events are influenced by both probabilistic (hazard) and deterministic (vulnerability) factors.
• Quantifying these factors is crucial for developing targeted flood management strategies.

Purpose of the Study:

• To establish guidelines for flood adaptation strategies by simultaneously considering probabilistic and deterministic factors.
• To model flood occurrence and classify municipalities based on these factors to inform adaptation planning.

Main Methods:

• Investigated 1795 Japanese municipalities, modeling flood occurrence from 2010-2019 using government statistics.
• Utilized rainfall indicators as probabilistic factors and terrain/land use as deterministic factors.
• Employed nonhierarchical clustering to categorize municipalities into six distinct clusters based on quantified factors.

Main Results:

• Successfully classified Japanese municipalities into six clusters based on combined probabilistic and deterministic flood risk factors.
• Demonstrated the feasibility of developing tailored adaptation strategies for each cluster.
• Identified specific recommendations, such as reinforcing structural measures in high-risk increase clusters and enhancing existing measures in stable clusters.

Conclusions:

• A simultaneous consideration of probabilistic and deterministic factors provides a robust framework for flood adaptation planning.
• Cluster-based strategies enable targeted interventions, optimizing the allocation of resources for climate adaptation.
• This approach supports the development of resilient communities against increasing flood risks under climate change.