In the rugged terrain of the Eastern Himalayan Mountain Region, specifically the Papumpare District of Arunachal Pradesh, India, a groundbreaking study has shed new light on landslide hazards, offering critical insights for the energy sector and beyond. Led by Tilling Riming, Praduyt Dey, Santanu Kumar Patnaik and Manju Narzary, this research, published in ‘Nature Environment and Pollution Technology’ (which translates to ‘Nature Environment and Pollution Technology’), employs advanced geospatial techniques and multicriteria decision-making (MCDM) to map landslide susceptibility zones with unprecedented accuracy.
The team utilized the Analytical Hierarchy Process (AHP), a robust MCDM model, to evaluate eight key parameters: Slope, Rainfall, Drainage Density, Lineament Density, Geomorphology, Soil, Geology, and Land use/Land cover. These factors were meticulously analyzed using ArcGIS 10.8 software and ERDAS IMAGINE 2014, resulting in a detailed landslide susceptibility zone map. The region was then classified into five distinct zones, from high to low susceptibility, with the most critical areas identified near steep and disturbed slopes, often altered by earth-cutting activities for construction or road building.
The implications for the energy sector are profound. “Our findings highlight the need for careful planning and mitigation strategies, especially in areas with high landslide susceptibility,” said Tilling Riming. “This is crucial for the energy sector, where infrastructure projects often involve significant earthworks and can be particularly vulnerable to landslides.”
The study’s validation, using the Receiver Operating Characteristic (ROC) curve, yielded a 73.2% accuracy rate, underscoring the model’s reliability. This high performance suggests that the model could be a game-changer for future developments in landslide hazard management. By identifying high-risk areas, energy companies can better plan their projects, mitigate risks, and protect both their investments and the environment.
The research not only enhances our understanding of landslide hazards but also provides a blueprint for future studies. As Santanu Kumar Patnaik noted, “This approach can be replicated in other hilly terrains, offering a comprehensive tool for landslide hazard management and mitigation strategies.”
As the energy sector continues to expand into challenging terrains, this research offers a beacon of guidance. By integrating advanced geospatial techniques and MCDM models, the study paves the way for more informed decision-making, ultimately shaping a safer and more sustainable future for infrastructure development in landslide-prone regions.
