Landslide Multi-Hazard Risk Assessment, Preparedness and Early Warning in South Asia: Integrating Meteorology, Landscape and Society

About 12.6% of Indian land mass is prone to landslides, with the Himalaya and Western Ghats regions particularly prone due to climate, geomorphology & geology. Rainfall and earthquakes are the main triggers of these landslides. Poor land management practices (e.g., deforestation, slash & burn cultivation, haphazard mining and heavy tilling in agriculture), coupled with increased development and poor settlement location have increased vulnerability of communities in these areas to landslides.

The impact of landslides on people, business, culture and heritage can be considerable and wide-ranging, including fatalities, loss of agricultural land and infrastructure, and damage to ecosystems. To build resilience to landslides in these vulnerable communities (a key aim of SHEAR), a root and branch evaluation of human interactions with landslide prone environments, and improved knowledge of the 'physical' processes is required. Developing approaches to integrate weather, landscape and social-dynamic models is fundamental to building an effective hydrologically-controlled landslide early warning system (EWS).

LANDSLIP will develop new insights by building on existing scientific research in India, the UK and Italy and using interdisciplinary methodologies and perspectives. Due to complex environmental conditions and triggering processes that cause landslides, the extent and variability of spatial & temporal scales means that landslides are inherently difficult to forecast and manage at site, slope, catchment and regional spatial scales and hourly to decadal temporal scales. LANDSLIP will address this by doing research to understand weather regimes (previously not done in S Asia) and rainfall characteristics that trigger landslides and geomorphological/geological control factors that can enhance landslide susceptibility. Knowledge of where and when historic landslides have occurred and under what environmental conditions, will also be collated and analysed, drawing on extensive consortium experience of developing and managing landslide inventories and impact libraries.

An innovative challenge we address in LANDSLIP is how slope and site specific EWS inform wider catchment to national landslide EWS and how early warning information from medium-range forecasts supplement and enhance short-term (day to a week) forecasting approaches.

A further innovative aspect of LANDSLIP is improving EWS effectiveness through integrating social dynamics information gathered from both 'Human' (i.e. social media) and physical sensors (remote sensing and pre-existing site-specific wireless networks deployed by AMRITA). LANDSLIP will develop ways of utilising these sources of information to supplement existing inventories and enhance EW information for decision makers.

Our programme will operate in partnership with decision makers, in public and private sectors, academics and non-for profit agencies to achieve an overarching aim of contributing to better landslide risk assessment and early warning, in a multi-hazard framework in India, aiming to increase resilience and reduce loss. Tools and services, focussed on a web map interface, will be developed in conjunction with local scientists, decision makers and communities to improve resilience to hydrologically-controlled landslides in India, specifically using two pilot study areas; Darjeeling-East Sikkim in the Himalaya and Nilgiris in the Western Ghats. We will ensure knowledge transfer to other vulnerable communities by assessing how they can be applied, remotely, in Afghanistan.

Through advances in interdisciplinary science and application in practise, the collective ambition of this consortium is to contribute to better landslide risk assessment and early warning in a multi-hazard framework, and, by working with communities, better preparedness for hydrologically controlled landslides and related hazards on a slope to regional spatial scale and daily to seasonal temporal scale.

Our research holds potential for significant impact both in India and across and beyond South Asia.

In the short term at community & sub-national level (in 2 pilot locations) we will benefit a wide range of actors affected by or responsible for landslides via (i) inclusion of meteorological, landscape and social data in landslide risk management; (ii) application of weather regimes and probabilistic forecasts (iii) improved knowledge on assessing and managing landslide multi-hazards, (iv) improved knowledge on effectively methods for communicating landslide risk information, including opportunities to utilise appropriate technology (a web-mapping service, phone applications and SMS protocol); (v) enhanced management of complex data for improved landslide inventories, (vi) improved knowledge on how to develop landslide EWS at slope and catchment scales; (vii) inclusion of the above in enhanced landslide risk assessment and early warning systems at sub-national level; (viii) provision of bespoke outputs tailored to specific user groups, supported by additional decision support tools to ensure the improvements in knowledge, tools and products translate into changed policy and practice.

We will look to scale enhancements in hazard resilience at state and national levels through supporting key actors responsible for landslide risk management (including Geological Survey of India, State and National level Disaster Management Authorities) to apply lessons first at sub-national level (in pilot locations) and then support them in taking best practices to national level. This will be complemented with coordinated outreach to relevant actors active at sub-national level in other states. We will also look to scale enhancements in hazard resilience at regional level, in particular through supporting Indian agencies to provide intra-regional capacity support and knowledge exchange, specifically through building partnerships between Indian agencies and Afghanistan practitioners who have expressed interest (and commitment see letters of support) in learning from Indian peers to enhance Afghan landslide risk management.

Our demand-driven approach will ensure effective co-production of knowledge with end users, delivering outcomes that are fit for purpose, of appropriate scale, language, format and content, are understandable and useable, and match with concerns and priorities of diverse user groups. We will also consider the translation of landslide risk information "towards information that is understandable and actionable by different kinds of users: in other words, risk knowledge" (UNISDR 2015), prioritising translation and interpretation of landslide risk information into clear "recommendations or plans of action to be taken up by decision-makers" (CDKN 2014). We are aware of the tendency for hazard specific risk information to be disregarded by actors with sectoral agendas (e.g., health, employment, housing) if not first contextualised and translated in terms of clear relevance to their sector (CDKN 2014) and will be proactive is tailoring knowledge, tools and outputs to specific user groups.

Academic impacts include cutting-edge developments in meteorology, landslide hazard and risk assessment/EWS, and delivery of innovative technologies while educating a new generation of scientists. The research capacity, knowledge and skills of Indian researchers will be enhanced by embedment in UK partner institutes. Our research will be of wider interest to governance, insurance, geo-environmental and construction sectors. Social impacts with include the enhancement of landslide risk management, reduction in landslide related losses, and the resulting improvement in quality of life, health and well-being of communities affected by landslides in a multi-hazard framework.

CDKN (2014) Risk-Informed Decision-Making
UNISDR (2015) Concept Note for Working Session of UN World Conference on DRR (Sendai)