Engineering Geology Template


This paper presents the results of an extensive mapping of co-seismic landslides triggered by the 2015 Gorkha earthquake in central Nepal. More than 19,332 landslides have been identified covering 61.5 km2 of land in about 20,500 km2 area of investigation using Google Earth imagery. Their spatial distribution characteristics and relation to the triggering mechanism is studied. Interesting regional localization and angular distribution characteristics, more controlled by the rupture directivity is observed. Seismic, geomorphic and lithological parameters that induce their susceptibility is studied using two indices of landslide concentration: Landslide Area Percentage (LAP) and Landslide Number Percentage (LNP) in comparison with % area of each parameter classes. Positive correlation with the chosen triggering parameters are observed but there are some significant differences in the parameter values and distribution plots to co-seismic landslides in other parts of world. 
These results provide valuable information about the slope response characteristics in case of seismic activation in thrust faulting Himalayan landscapes, and this is important in further researches on co-seismic landslide prediction models for mountainous settlements, sediment yield studies and cascading landslide disasters after major earthquakes.


In mountainous regions, strong earthquakes trigger thousands of landslides in a wide area and in a short interval of time- a few minutes or hours, and continuously during the aftershocks for days. These landslides evolve a secondary chain of disasters eg. damage to settlements, landslide dams and flooding, blockade of lifelines and roads and damage to the infrastructure in a situation of emergency rescue and frequently occurring aftershocks (Cui et al., 2011). It is necessary to properly understand their nature of occurrence in relation to their triggering mechanism, which is a delicate interplay of the strong ground motion (e.g. fault plane geometry, rupture directivity and ground acceleration), geomorphological (e.g. absolute elevation, slope angle, slope orientation, curvature) and lithological characteristics at a site. This understanding is essential for the improvement of spatial earthquake induced landslide prediction models, which are critical to minimizing the hazard in mountainous areas with development and implementation of hazard maps and land-use policies (e.g. Xu et al., 2012; Dimri et al., 2007).
On 25 April 2015, at 11:56 am, Nepal Standard Time, a catastrophic earthquake Mw= 7.8 shook much of central Nepal, along the Main Himalayan Thrust fault and resulting over 8,856 fatalities and 22309 injured (Government of Nepal, 2016) .The main shock epicentre (28.147° N, 84.708° E) was located in Gorkha district, with focal depth ~15 km, which was followed by numerous aftershocks over the next several weeks (Adhikari et al., 2015; USGS, 2016). The earthquake triggered more than 19,332 landslides, avalanches, and rockslides above and near the rupture zone covering 61.5 sq. km area of landmass degradation and comprising the area of investigation (AOI)= 20,500 sq. km. Scrutinizing co-seismic landslide distribution is essential for understanding the nature of earthquakes in the region and predicting susceptible landslide areas in future earthquakes. Earlier studies of earthquake triggered landslide distribution and simple spatial correlation have been summarized by Keefer (1984, 1999, 2000, 2002) and Rodríguez (1999). The focus on the relation between the landslides and the triggering seismic factors- e.g. magnitude, distance to epicenter/fault rupture, peak ground acceleration (PGA) and static hill slope condition, geomorphologic factors- e.g. slope, aspect, curvature and geology is key to understanding their nature of occurrence. This has been analyzed after many large earthquakes e.g. Mw=6.6 Chuetsu, Japan-

(Wang et al., 2007); Mw=7.9 Wenchuan, China (Qi et al., 2010; Dai et al., 2011; Xu et al., 2014a); Mw=7.0 Port-au-Prince, Haiti (Xu et al., 2014b). Previous efforts of studies on landslides triggered by the Gorkha earthquake based on field reconnaissance have been compiled (e.g. Collins and Jibson, 2015; Hashash et al., 2015) and their spatial distribution characteristics with mapped 4312 coseismal landslides has been discussed (Kargel et al., 2016). However, this study considers larger number of mapped landslides (19,332) with area polygons and size >20m2.

The main purpose of this study is to characterize the spatial distribution of landslides triggered by the Gorkha earthquake and correlating their occurrence with the triggering mechanisms: strong ground motion (e.g. PGA, seismogenic-fault), geomorphology (e.g. slope, aspect, curvature) and lithology, using two proxies of the co-seismic landslide abundance- 1) landslide area percentage (LAP) and 2) landslide top number percentage (LNP) to the percentage of class area in each parameter within the Area of Influence AoI (i.e. 20,500 km2). The LAP is defined as % area of landslides out of total landslide area (i.e. 61.5 in the class area within AoI. The LNP is defined as % number of landslides out of total landslide number (i.e. 19,332) in the class area within AoI. Overall landslide area density, defined as % of landslide area to total area of investigation was found to be (61.5/20500*100% =) 0.3% and landslide number density is (19,332 nos. / 20,500 sq. km. =) 0.94 landslides per square kilometer.

2. Tectonic setting

The Gorkha earthquake ruptured along 120 km west-to-east of the Main Himalayan Thrust (MHT) (a shallow dipping megathrust) system (Grandin et al., 2015; Elliott et al., 2016), which is the main boundary interface between the sub ducting Indian plate and the overriding Eurasian plate to the north and accommodates half the India-Eurasia convergence -avg. 20mm/year (eg. Bilham et al., 1997; Bettinelli et al., 2006). Four major fault systems run east- west of region including main frontal thrust(MFT), main boundary thrust(MBT), main central thrust(MCT) and South Tibetan Detachment System (STDS) from south to north; the first three of which comprise the HFT system (Bollinger et al., 2006) and the fourth marks the boundary of Indian and Eurasian plate. The spatio-temporal evolution of aftershock epicenters reveals a clustering activity within the main shock rupture zone and narrow concentration in 40 km-wide band which is more seismically active towards the east (Adhikari et al., 2015).