Abstract:
Landslides are becoming more frequent and
destructive as the variability in climate and changes in the
natural environment intensified. Numerous studies have
considered geological, geomorphological, and human factors
in landslide susceptibility analysis. However, studies
considering subsurface hydrological processes in basin scale
for landslide susceptibility analysis are relatively rare. This
study investigated the importance of groundwater gradient as
a triggering factor along with six other influencing factors
belonging to four groups: topography, geological conditions,
hydrological environment, and human engineering activities
for landslide susceptibility in the Kegalle District area in Sri
Lanka. The groundwater flow model was developed using the
USGS modular finite-difference flow model (MODFLOW),
and the spatial distribution of hydraulic gradient was
estimated over a 1,523 km2 area. The estimated hydraulic
gradient was then combined with slope, elevation, distance
from the river, rainfall, land use, and soil texture for landslide
susceptibility analysis using the analytical hierarchy process.
The study area is divided into five groups, from low to high
risk of susceptibilities. The results show a 60%-75% match
between landslides that occurred in the past and the
categories with extreme hydraulic gradients. The final
landslide susceptibility map generated incorporating all other
influencing factors demonstrates an F1-score of 0.814,
highlighting the potential of the proposed methodology as a
valuable tool for disaster risk assessment and management.
Citation:
N. Wijayaweera and L. Gunawardhana, "Integrated Analytical Hierarchy Process and Numerical Groundwater Flow Modelling Approach for Mapping Landslide Susceptibility in Kegalle District, Sri Lanka," 2023 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2023, pp. 125-130, doi: 10.1109/MERCon60487.2023.10355508.