Rainfall Event–Duration Thresholds for Landslide Occurrences in China

Abstract

A rainfall threshold for landslide occurrence at a national scale in China has rarely been developed in the early warning system for landslides. Based on 771 landslide events that occurred in China during 1998–2017, four groups of rainfall thresholds at different quantile levels of the quantile regression for landslide occurrences in China are defined, which include the original rainfall event–duration (E–D) thresholds and normalized (the accumulated rainfall is normalized by mean annual precipitation) (EMAP–D) rainfall thresholds based on the merged rainfall and the Climate Prediction Center Morphing technique (CMORPH) rainfall products, respectively. Each group consists of four sub-thresholds in rainy season and non-rainy season, and both are divided into short duration (<48 h) and long duration (≥48 h). The results show that the slope of the regression line for the thresholds in the events with long durations is larger than that with short durations. In addition, the rainfall thresholds in the non-rainy season are generally lower than those in the rainy season. The E–D thresholds defined in this paper are generally lower than other thresholds in previous studies on a global scale, and a regional or national scale in China. This might be due to there being more landslide events used in this paper, as well as the combined effects of special geological environment, climate condition and human activities in China. Compared with the previous landslide model, the positive rates of the rainfall thresholds for landslides have increased by 16%–20%, 10%–17% and 20%–38% in the whole year, rainy season and non-rainy season, respectively.

The optimal rainfall thresholds and probabilistic rainfall conditions for a landslide early warning system for Chuncheon, Republic of Korea

“…Figure 10 graphically illustrates the formulation of E = 73.915D 0.2046 (21 ≤ D ≤ 167). This is a meaningful result because the optimal threshold was defined with a 12-h break between consecutive rainfalls, whereas in most of Graph showing the results of the two-dimensional Bayesian model for different rainfall durations and rainfall intensities the literature, a 24-h break is taken into account (Saito et al 2010;He et al 2020). The short time, such as a 12-h break, was chosen due to high permeability soil characteristics such as sandy loam and the topographical features of the landslide occurrence area consisting of a steep slope of 15°or more.…”

“…From the values of contingencies, we can calculate the probability of detection (POD), the probability of false detection (POFD), the probability of false alarm (POFA), and the Hanssen and Kuipers (1965) (HK) skill score (Table 2). Among them, the HK skill score (also known as Peirce's skill score) is defined as the POD minus the POFD (Peirce 1884;Hanssen and Kuipers 1965). Besides, the Euclidean distance from optimal classification (δ) is calculated by adding SQRT to the sum of the square of POFD and the square of 1 minus POD ( Table 2).…”

Satellite rainfall products outperform ground observations for landslide prediction in India

“…In this analysis, ERA5 (Hersbach et al, 2020) is chosen as a reference rainfall product for estimating the integration weights. The integration between IMERG-ER and SM2R is the PMERG-D (daily) dataset.…”

InSAR Monitoring of Landslide Activity in Dominica

“…In addition to better understanding the pre-landslide conditions for use in the prediction of future landslide risk, landslide-inducing rainfall thresholds are also used [59][60][61][62]. For Dominica, a rainfall threshold was calculated by linking daily rainfall measurements (between 1977 and 2013) recorded from two rain gauges (one on the east side of the island, and one on the west side) with the days in which landslides were documented [6].…”