Landslides Triggered by the 2016 Heavy Rainfall Event in Sanming, Fujian Province: Distribution Pattern Analysis and Spatio-Temporal Susceptibility Assessment

Author:

Ma Siyuan12,Shao Xiaoyi34,Xu Chong34ORCID

Affiliation:

1. Institute of Geology, China Earthquake Administration, Beijing 100029, China

2. Key Laboratory of Seismic and Volcanic Hazards, Institute of Geology, China Earthquake Administration, Beijing 100029, China

3. National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China

4. Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China

Abstract

Rainfall-induced landslides pose a significant threat to the lives and property of residents in the southeast mountainous area. From 5 to 10 May 2016, Sanming City in Fujian Province, China, experienced a heavy rainfall event that caused massive landslides, leading to significant loss of life and property. Using high-resolution satellite imagery, we created a detailed inventory of landslides triggered by this event, which totaled 2665 across an area of 3700 km2. The majority of landslides were small-scale, shallow and elongated, with a dominant distribution in Xiaqu town. We analyzed the correlations between the landslide abundance and topographic, geological and hydro-meteorological factors. Our results indicated that the landslide abundance index is related to the gradient of the hillslope, distance from a river and total rainfall. The landslide area density, i.e., LAD increases with the increase in these influencing factors and is described by an exponential or linear relationship. Among all lithological types, Sinian mica schist and quartz schist (Sn-s) were found to be the most prone to landslides, with over 35% of landslides occurring in just 10% of the area. Overall, the lithology and rainfall characteristics primarily control the abundance of landslides, followed by topography. To gain a better understanding of the triggering conditions for shallow landslides, we conducted a physically based spatio-temporal susceptibility assessment in the landslide abundance area. Our numerical simulations, using the MAT.TRIGRS tool, show that it can accurately reproduce the temporal evolution of the instability process of landslides triggered by this event. Although rainfall before 8 May may have contributed to decreased slope stability in the study area, the short duration of heavy rainfall on 8 May is believed to be the primary triggering factor for the occurrence of massive landslides.

Funder

National Key Research and Development Program of China

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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