Prediction of a multi-hazard chain by an integrated numerical simulation approach: the Baige landslide, Jinsha River, China

Abstract

Successive major landslides during October and November 2018 in Baige village, eastern Tibet, dammed the Jinsha River on two occasions, and the subsequent dam breaches instigated a multi-hazard chain that flooded many towns downstream. Analysis of high-resolution aerial images and field investigations unveiled three potentially unstable rock mass clusters in the source area of the landslides, suggesting possible future failures with potential for river-damming and flooding. In order to evaluate and understand the disaster chain effect linked to the potentially unstable rock mass, we systematically studied the multi-hazard scenarios through an integrated numerical modelling approach. Our model begins with an evaluation of the probability of landslide failure, including runout and river damming, and then addresses the dam breach and resultant flood-hence simulating and visualising an entire disaster chain. The model parameters were calibrated using empirical data from the two Baige landslides. Then, we predict the future cascading hazards via seven scenarios according to all possible combinations of potential rock mass failure. For each scenario, the landslide runouts, dam-breaching, and flooding are numerically simulated with full consideration of uncertainties among the model input parameters. The maximum dam breach flood extent, depth, velocity, and peak arrival time are predicted at sequential sites downstream. As a first attempt to simulate the full spectrum of a landslide-induced multi-hazard chain, our study provides insights and substantiates the value provided by multi-hazard modelling. The integrated approach described here can be applied to similar landslide-induced chains of hazards in other regions.

Controls on the formation and size of potential landslide dams and dammed lakes in the Austrian Alps

“…We compare the geomorphometric parameters (Table 1) of our modeled landslide dams to those of landslide dams from existing inventories (Table 2). Except for Fan et al (2012) and Tacconi Stefanelli et al (2015), these studies focus on river-damming landslides only. Various indices have been developed to predict the ability of a landslide to dam a valley and the longevity of the dam.…”

“…Alps, Austria a (this paper) 7.7 × 10 4,b 9.9 × 10 7 0.0 7.9 × 10 7 0|3 c 75|155 c 1057 Alps, Austria (Dufresne et al, 2018) 1.5 × 10 7 2.1 × 10 9 0.0 1.1 × 10 9 40 450 5 Apennines, Italy (Tacconi Stefanelli et al, 2016) 3.0 × 10 4 1.1 × 10 8 ---> 100 300 Taiwan (Chen et al, 2014) 6.0 × 10 2 5.0 × 10 8 --3 300 64 Wenchuan, China (Fan et al, 2012) -7.5 × 10 8 4.2 × 10 3 2.1 × 10 7,d 1 160 828 New Zealand (Korup, 2004) 4.0 × 10 4 2.7 × 10 10 1.0 × 10 4 5.0 × 10 9 5 800 232 Japan (Korup, 2004) 3.0 × 10 3 1.2 × 10 9 2.0 × 10 3 6.0 × 10 8 --USA (Korup, 2004) 1.9 × 10 3 1.5 × 10 9 1.0 × 10 3 5.5 × 10 8 --Worldwide (Korup, 2004) 4.3 × 10 3 1.3 × 10 9 2.0 × 10 3 4.0 × 10 9 --184 Worldwide (Costa and Schuster, 1988) 7.0 × 10 4 2.8 × 10 9 1.1 × 10 5 6.8 × 10 8 3 550 225 Worldwide (Fan et al, 2020) 1.2 × 10 3 5.0 × 10 9 0.0 1.6 × 10 10,e 2 1000 443 f a Modeled landslide dams and lakes. b The modeled landslides with volume below 10 5 m 3 were not computed.…”

“…coined by Ermini and Casagli (2002), considers the dam height, allowing one to indirectly take into account the steepness of the dam flanks. Korup (2004) introduced two new indices also based on landslide dam height, the backstow index (Is) and the basin index (Ia):…”

“…Thus, most landslide dam and lake inventories only contain relatively large dams. Several geomorphometric indices have been developed to quantify the probability of landslides obstructing the valley and the stability of the resulting dams (Swanson et al, 1986;Canuti et al, 1998;Ermini and Casagli, 2002;Korup, 2004;Tacconi Stefanelli et al, 2016). However, studies on the formation of landslide dams and lakes, and on its dependence on factors that influence topography, such as contributing drainage area of rivers at their damming location, geologic preconditioning and long-term climatic forcing, are scarce.…”

“…A.-L. Argentin et al: Formation and size of potential landslide dams and dammed lakes Contributing drainage area at the damming position has been considered an important variable in computing obstruction and stability indices (e.g., Ermini and Casagli, 2002;Korup, 2004;Tacconi Stefanelli et al, 2016;Swanson et al, 1986). This attention to drainage area is due to the long-term evolution of mountain landscapes: drainage area, as a proxy for discharge, is related to river flow length (Hack, 1957), channel slope (Flint, 1974) and river width (Finnegan et al, 2005;May et al, 2013).…”