Usability of existing global and national data for flood related vulnerability assessment in Indonesia

Public climatic data are rapidly growing in volume and complexity at global and national scales but these data remain underutilized for vulnerability assessment. We aim to explore how flood records from Dartmouth Flood Observatory, a global flood monitoring database, can be linked with a national disaster database maintained by the Indonesian National Board for Disaster Management, to aid local vulnerability assessment in Indonesia. We focused on physical damage to structures and agricultural crops from flooding and examined spatiotemporal patterns of a vulnerability metric derived from principal component analysis. We identified the most vulnerable areas based on emerging hot spot analysis and detected sporadic hotspots (i.e. on again then off again) of flooding in Jakarta and West Java. Using our derived metric, we identified oscillating cold spots (i.e. a cold spot that was previously a hot spot) of vulnerability in Banten, Jakarta, West Java, and Central Java. The detection of nonhomogeneous spatiotemporal trends in flooding and vulnerability demonstrate potential usability of public climate data and help to outline directions for novel research.