Introduce a framework for landslide risk assessment using geospatial analysis: a case study from Kegalle District, Sri Lanka

Abstract

Landslides have become a frequent natural hazard and pressing severe environmental issues in Sri Lanka. The upward trend in high-intensity rainfall events, growing population, expansion of plantation, and lifelines increased the landslide risk of the country. Though developed countries adopted in risk assessment-based management, conversely, they rely on conventional landslide hazard assessment-based risk management. Therefore, this study is attempted to create a standardized landslide risk assessment framework, combining susceptibility and vulnerability. In the experimental design, landslide susceptibility was determined by nine (09) landslide causative factors, and fourteen (14) factors assessed for landslide vulnerability. Factors were prepared, standardized, and analyzed according to the level of contribution to susceptibility and vulnerability by using spatial multi-criteria evaluation method and entropy method under geographical information system. Spatial distribution of susceptibility and vulnerability were integrated to obtain the spatial distribution of risk. Analyses indicate that highly susceptible and high vulnerable areas are not demonstrated a high level of risk individually. However, a combination of them creates a high level of risk. The risk was classified into six classes, such as highest, high, moderate, low, lowest, and no risk. The highest-risk and high-risk zones of the area show 257 km2 (15%) and 21% (350 km2) of the total land area, respectively. Moderately risk zones take part 27% (446 km2). However, 22% (375 km2) of land area categorized as low or lowest risk and 15% (255 km2) under the no-risk. The study concluded that the developed framework is transparent and easy to update periodically by the local authorities. Hence, public policymakers can use the findings of this study to plan the future development of the region and the country. In contrast, risk assessment provides essential information to enhance national disaster risk reduction strategies.