LANDSLIP

View of landslide-prone slopes in Sikkim, India

Role in SHEAR

To improve the reliability of landslide multi-hazard risk assessment and early warning.

Landslides in India

Landslides are mainly triggered by heavy rainfall and earthquakes, and the risks are increased by human activity and poor land-management practices.

About 12.6 per cent of the Indian landmass is prone to landslides with the climate, geomorphology and geology of regions contributing to their vulnerability.

LANDSLIP focuses on two case study regions:

  • Nilgiris District, southern India
  • Darjeeling and East Sikkim districts, Himalaya

The Nilgiris District is 2566 km2 and has a population of about 0.8 million. It is one of the most landslide-prone regions in Tamil Nadu State, India.

The Darjeeling District covers 3232 km2 and has a population of about 1.9 million, with 75 per cent of its area prone to landslides. East Sikkim covers 955 km2, all landslide prone, with a population of 0.3 million.

In both regions, deforestation, slash-and-burn cultivation, mining, heavy tilling, increased development and growing settlements have all contributed to growing risks posed to communities by landslides.

The devastation caused by landslides includes fatalities, injury, and damage to homes, livelihoods and vital infrastructure.

Aims

LANDSLIP is working to build resilience to and reduce loss caused by landslides in these vulnerable communities by:

  • working across scientific disciplines to improve landslide risk assessment and early warning in a multi-hazard framework
  • working with communities to improve preparedness for hydrologically controlled landslides and related hazards

Approach

  • Consider spatial scales, from specific slopes to wider regions.
  • Consider temporal scales, from daily to seasonal.
  • Operate in partnership with decision makers in public and private sectors, academia and not-for-profit agencies.
  • Develop new insights by building on existing scientific research in India, the UK and Italy, using interdisciplinary methodologies and perspectives.

Innovation

  • Conduct research into weather regimes that has never been conducted in South Asia before in order to understand the rainfall, geomorphological and geological factors that trigger and enhance landslides.
  • Address how slope and site-specific, early-warning systems can inform early-warning systems at larger catchment and national scales, and how medium-term forecasting approaches can enhance shorter-term forecasting approaches.
  • Integrate social-dynamic information gathered from social media to supplement existing landslide inventories and enhance early-warning system information for decision makers.
  • Develop tools and services with local scientists, decision makers and communities that will be applied to a web map interface, to support resilience to hydrologically controlled landslides.
  • Ensure knowledge transfer to other vulnerable communities by assessing how these tools can be applied remotely in Afghanistan.