Evaluation of cumulative rainfall and rainfall event-duration threshold based on triggering and non-triggering rainfalls: Northern Thailand case

A recently introduced rainfall threshold for landslide early warning systems combined a cumulative rainfall threshold with a rainfall event-duration (ED) threshold. Cumulative rainfall with rainfall event-duration, known as the CED threshold, was reported to perform better than the conventional ED threshold. However, the establishment of the CED threshold was based on a frequentist approach which required an adequate number of landslide-triggering rainfall data. An alternative to the use of landslide-triggering rainfall data is the use of non-triggering rainfall data. These rainfall events supply much bigger amount of data to the susceptibility model. Although the establishment of a rainfall threshold based on non-triggering rainfall events is seldom considered, previous scholars reported that this approach has produced better results than the conventional approach based on landslide-triggering events. This study investigates the reliability and prediction performance of the CED threshold based on non-triggering rainfall data. The performance of this threshold, designated as the negative-CED (CEDN) threshold, was compared with the positive-CED (CEDP) threshold based on landslide-triggering rainfall data. North Thailand, a landslide hot spot, was chosen as the study area. The proposed threshold was assessed from three skill scores, including (1) the true positive fraction (TPF), (2) the false positive fraction (FPF), and (3) the positive predictive value (PPV), and their variations over the range of threshold uncertainties. Rather than possessing lower uncertainties of the threshold parameters, the negative threshold provided better compromise predictions of TPF and FPF scores than the positive thresholds. Integrating the cumulative rainfall threshold and an event-based rainfall threshold resulted in a significant improvement in FPF scores, and hence enhanced the compromise predictions of TPF and FPF scores. Keeping in mind that the negative thresholds were not established from landslide data, care must be taken when using these thresholds and it is recommended that they should be applied only to areas where landslide data are limited.