Ground surface topography influences the spatial distribution of earthquake-induced ground shaking. This study shows the influence of topography on seismic amplification during the 2005 Kashmir earthquake. Earth surface topography scatters and reflects seismic waves, which causes spatial variation in seismic response. We performed a 3-D simulation of the 2005 Kashmir earthquake in Muzaffarabad with the spectral finite-element method. The moment tensor solution of the 2005 Kashmir earthquake was used as the seismic source. Our results showed amplification of seismic response on ridges and de-amplification in valleys. It was found that slopes facing away from the source received an amplified seismic response, and that 98 % of the highly damaged areas were located in the topographically amplified seismic response zone.

It remains elusive why there was only weak and limited ground shaking in Kathmandu valley during the 25 April 2015 Mw 7.8 Gorkha, Nepal, earthquake. Our spectral element numerical simulations show that, during this earthquake, surface topography restricted the propagation of seismic energy into the valley. The mountains diverted the incoming seismic wave mostly to the eastern and western margins of the valley. As a result, we find de-amplification of peak ground displacement in most of the valley interior. Modeling of alternative earthquake scenarios of the same magnitude occurring at different locations shows that these will affect the Kathmandu valley much more strongly, up to 2–3 times more, than the 2015 Gorkha earthquake did. This indicates that surface topography contributed to the reduced seismic shaking for this specific earthquake and lessened the earthquake impact within the valley.

Slowly moving active landslides threaten infrastructure, particularly along highway routes traversing active mountainous ranges. Detecting and characterizing such landslides in highly elevated mountainous terrains is challenging due to their inaccessibility, wide area coverage, limited approaches, and the complex nature of mass movements. In this study, we processed Sentinel-1 Synthetic Aperture Radar data acquired from 2015 to 2024 to detect active landslides along the Karakoram Highway alternate route (Chitral-Gilgit) and the Karakoram Highway part (Gilgit-Khunjerab). We detected 1037 active landslides in the study region using phase gradient stacking and a deep learning network. Based on the detection, we applied time series InSAR analysis to reveal the velocity and deformation series for some large-scale landslides, revealing high displacement rates with line-of-sight velocities reaching up to −81 mm/yr. We validated our detections by comparing them with Google Earth imagery and the previously published landslide inventories along the Karakoram Highway. This study reveals the spatial distribution of active landslides along the uplifted mountainous terrain, highlighting potentially unstable zones, and offers insights into hazard mitigation and risk analysis, especially for less monitored economic roads in orogenic zones.

Seismic hazard analysis is carried out in this study by estimating ground motion for hypothetical earthquakes in the area of Muzaffarabad, Pakistan, with the MT solution of the 2005 Kashmir earthquake. The earth’s topography influences seismic waves by scattering and reflecting it, thereby causing spatial variation in seismic response. Using the moment tensor solution of the 2005 Kashmir earthquake, we perform 25 spectral element method (SEM)-based 3D simulations along major faults in the study area. The SEM model incorporates the topography and homogeneous half-space characteristics. Our results show that, beside topography, the relative location of the source with respect to slopes also has an influence on the observed variation in ground shaking amplitudes. By integrating the mean and standard deviation of estimated ground shaking from 25 simulations, we present a seismic hazard map for the study area. The map summarizes the topographic and potential source location effect on seismic-induced ground shaking in the study area. It provides a classification from hazardous to safe in relative terms and can be used as a guide in earthquake preparedness.

The Hindukush region in Northwest Pakistan is a mountainous area that often faces natural disasters, such as landslides, flash floods, glacial lake outbursts, and debris flow, that alter the landscape and damage property. This study focused on the Chitral area of the Hindukush region to assess the landslide distribution and susceptibility using field observations and factor analysis. Nine landslide causative factors were selected and weighted using Geographic Information System (GIS)-based Frequency Ratio (FR) and Analytical Hierarchy Process (AHP) techniques. The factors included slope, aspect, rainfall, land cover, lithology, seismicity, distance to faults, streams, and roads. Landslide susceptibility maps were generated and classified into five categories: very high, high, moderate, low, and very low. Various landslides were observed in the field comprising debris flow, debris slide, soil erosion, and rockfall. Rockfall in the study area indicates active seismicity in the Hindukush region. Furthermore, the area under the curve method validated the results, which gave 0.80 for FR and 0.73 for AHP. The results showed that most of the landslides in the study area were caused by steep slopes of mountains, followed by precipitation. The high landslide susceptibility zones in the study area matched well with the field-based landslide collections, which showed the reliability of the mapping methods. These findings can help plan and implement measures in the Hindukush region to reduce the risk and impact of landslides, such as early warning systems, slope stabilization, land use regulation, and evacuation plans.