Modeling impacts on food security from debris flows
Implementing Partner: Build Change
Project name:Modeling impacts on food security from debris flows in India
This research employs machine learning and Google Earth Engine to create an online GIS-based tool that enhances intervention accuracy for food security.
It examines how debris flow disruptions in mountainous road networks cascade to impact food resilience, bridging a critical knowledge gap.
By mapping these vulnerabilities, the study informs strategies to reinforce supply chains and road infrastructure, ensuring adaptive solutions that strengthen food security in mountain regions facing climate and disaster-related disruptions.
disasters in the Himalayas
(1985–2014)
risk from high-volume
landslides and avalanches
Impact
1
This project establishes a framework to assess road network vulnerabilities and their cascading effects on food supply chains, delivering key insights to strengthen resilience in mountainous regions frequently impacted by debris flow hazards and transport disruptions.
2
Centered on the Eastern Himalayas, this study integrates debris flow hazard modeling, transport disruption analysis, and food security assessment to develop a robust framework for strengthening road infrastructure and stabilizing supply chains in disaster-prone mountain regions.
3
Using advanced machine learning algorithms, this research optimizes emergency supply prepositioning, enhancing disaster response efficiency and reinforcing community resilience. By mitigating road network disruptions in mountain areas, it ensures timely resource distribution and adaptive crisis management.
