Cambodia faces significant challenges from climate-induced disasters, particularly floods and droughts. These natural calamities have cost the country an average of $148 million annually over the past two decades and continue to threaten its socio-economic development. As climate change accelerates, such events are becoming more frequent and severe, potentially reducing Cambodia’s GDP by 3.0% to 9.4% by 2050. To address these challenges, Cambodia is leveraging artificial intelligence (AI) and geospatial technologies to enhance its disaster risk analysis and resilience.
Understanding the Impact of Floods and Droughts in Cambodia
Floods and droughts are among the most devastating disasters in Cambodia, severely affecting its agriculture-based economy and vulnerable populations. For instance:
- Floods damage infrastructure, destroy crops, and displace families. In September 2024 alone, floods affected 45,335 families, damaged 18,962 houses, and destroyed 18,213 hectares of rice fields.
- Droughts, on the other hand, lead to water shortages, failed harvests, and loss of livelihoods, especially in areas dependent on agriculture.
These disasters are most prevalent in regions such as the Tonle Sap Lake, the Mekong River, and the southern plains, where a significant portion of the population and agricultural land is at risk.
The Role of AI in Disaster Risk Management
To mitigate the impacts of these disasters, the National Disaster Management Committee (NDMC), in collaboration with the United Nations World Food Programme (WFP), is using cutting-edge technologies like AI and geospatial systems. These technologies enable detailed risk modeling by analyzing climate hazards, exposure, and vulnerability.
According to data from the National Disaster Management Committee,As of September 2024, floods have impacted 21 provinces and capitals in Cambodia. These include:
- Northwest: Battambang, Pursat, Banteay Meanchey, Pailin, and Siem Reap.
- Central Plains: Kampong Thom, Kampong Cham, Tbong Khmum, Prey Veng, and Kandal.
- Northeast: Preah Vihear, Oddar Meanchey, Mondulkiri, Ratanakkiri, Kratie, and Stung Treng.
- Coastal Areas: Sihanoukville and Koh Kong.
- Southwest: Kampong Speu and Svay Rieng.
- Capital: Phnom Penh.
Key Concepts in Risk Modeling:
- Climate Hazards: Events like floods or droughts that cause damage and disruptions.
- Exposure: The presence of people, assets, or infrastructure in risk-prone areas.
- Vulnerability: The socio-economic capacity to cope with and recover from disasters.
AI algorithms, particularly Random Forest (RF) models, process extensive datasets to identify high-risk areas, while geospatial technologies provide detailed maps and real-time data.
Geospatial Technologies Empowering Decision-Making
Advancements in geospatial tools have revolutionized climate risk analysis. Google Earth Engine (GEE), a cloud-based platform, plays a pivotal role in this effort. GEE enables researchers to:
- Access satellite imagery and geographic data from multiple sources.
- Integrate external data for more comprehensive risk analysis.
- Use machine learning algorithms to predict disaster patterns.
These tools allow Cambodia to produce detailed, localized risk maps, essential for targeted disaster planning and response.
Findings from AI-Powered Analysis
Using AI and geospatial technologies, Cambodia has uncovered critical insights into flood and drought risks:
- Flood Risks: Around 15% of the population and 16% of agricultural land are highly vulnerable.
- Drought Risks: Approximately 29% of the population and 33% of agricultural land face significant threats.
These findings highlight the urgent need for targeted interventions in high-risk provinces, including Battambang, Pursat, Siem Reap, and Kampong Thom, among others.
Benefits of AI in Disaster Risk Reduction
- Improved Risk Assessment: AI provides a more detailed understanding of disaster risks, enabling precise identification of vulnerable areas.
- Data-Driven Planning: Local governments can use AI-generated insights for effective resource allocation and emergency planning.
- Enhanced Early Warning Systems: Real-time data from AI models can improve early warning systems, reducing the loss of lives and property.
- Support for Resilient Development: Risk-informed decision-making ensures infrastructure and policies are designed to withstand future climate shocks.
Challenges and the Way Forward
While AI offers immense potential, Cambodia faces challenges in fully implementing these technologies, such as:
- Data Gaps: Limited access to high-quality historical and real-time data.
- Technical Expertise: The need for skilled personnel to manage AI systems and interpret results.
- Resource Constraints: Financial and infrastructural limitations hinder the widespread adoption of AI tools.
To address these issues, Cambodia must invest in capacity building, foster international partnerships, and allocate resources to expand AI and geospatial technology adoption.
A Promising Path Toward Resilience
By integrating AI and geospatial technologies into disaster risk management, Cambodia is taking significant strides toward building resilience against climate-induced disasters. These efforts are crucial for protecting lives, preserving livelihoods, and ensuring sustainable development in a climate-vulnerable region.
What are your thoughts on using AI for disaster management? Share your insights and ideas in the comments below!
