Dataset and codes to analyze the effects of FAR and MER on flood damage: case study of the 2018 Japan Floods

The dataset and R codes to investigate the effects of the false alarm ratio (FAR) and missed event ratio (MER) on flood damage by applying Bayesian regression analyses to open data on the 2018 Japan Floods in 127 municipalities in four prefectures (i.e., Okayama, Hiroshima, Ehime, and Fukuoka). The data for FAR and MER were collected from the real-time flood warning map (Kouzui Kikikuru in Japanese) during the 2018 Japan Floods, which provides limited open data on warning performance. The data for disaster damage, namely (1) fatalities, (2) injuries, (3) economic losses to general assets, and (4) economic losses to crops during the 2018 Japan Floods, were collected from technical disaster damage reports compiled by the prefectures and the Cabinet Office. Additional detailed instructions are provided in a readme file.