Extreme-rainfall Data as a Basis for Landslide Warnings: a Case Study of a Road in Central Taiwan. Issue 1 (June 2021) - Lin, Ji-Yuan; Chao, Jen-Chih; Wu, Cheng-Lin; Hsieh, Wei-Fang
Abstract: In recent years, an increase in extreme rainfall events linked to global warming has led to increases in the number and intensity of disasters such as landslides, landslips, and debris flows in Taiwan. This study focuses on the impact of such events, especially during typhoons, on County Road 89: the main traffic artery in Renai Township, Nantou County. Specifically, it will use an inverse distance weighting method (IDW) to analyze how rainfall at the four rainfall stations in Nantou, located at Renai, Ruiyan, Cuiluan and Cuihua, may related to damage events at the 12.3k, 22.53k, 32.5k, 46.3k, and 49k points on County Road 89. Then, landslide road-damage warning ranges will be drawn up using various combinations of data, including cumulative rainfall, maximum rainfall within a 24-hour period, and I-R alert model (I: rainfall intensity, R: cumulative rainfall), with an I-T alert model (I: rainfall intensity, T: rainfall duration) for comparison. This will yield an optimal warning value for the landslide-prone area of the focal road. Finally, data from County Road 89 will be compared against data from the Lishan landslide area, to ascertain whether/how such warning values should differ across geographic areas. The results are expected to usefully inform follow-up disaster prevention planning as well as further academic research on this topic.