With increased global warming, millions are projected to become climate refugees. As organizations seek ways to assist such populations, correctly predicting the movements of these individuals has become one of the biggest challenges. While many have claimed that forecasting models have been solved, the complexity involved in predicting the patterns of climate refugees need further research and development.
The Current State of Refugee Forecasting
Scientists have developed some forecasting tools for refugee movements, particularly for those people fleeing due to armed violence. It includes one that was recently published in Nature Scientific Reports, using an agent-based model to simulate individual refugee decisions based on simple rules derived from scientific insights. This type of approach has shown promising results: for the historical cases from Burundi, the Central African Republic, and Mali, it correctly predicted the destinations for more than 75% of the refugees.
Limitations of Existing Models
These models have demonstrated several capabilities and accuracies in the retrospective analysis of refugee movements but face the following challenges in forecasting future refugee movements:
Assumptions and Uncertainties: Any model is based on assumptions of the availability of a transport mode or safety considerations. The assumptions made would have to be highly tested and validated in the forecast.
Interdependent Forecasting: Refugee movement forecasting is interdependent on many related factors, such as the development of hostilities, market prices, and political decisions.
Lack of Training Data: Most machine learning algorithms suffer from a problem of incomplete or biased data; thus, they cannot predict the movement of refugees in cases of sudden disrupting events.
The Road Ahead for Climate Refugee Forecasting
Improvement of the forecasting models for refugees becomes increasingly significant at a time when the world is grappling with the impending climate crisis. According to the researchers, agent-based models-not requiring any historical training data-would be more useful in the predictions of mass movements of climate refugees. But significant work is yet to be done for developing accurate and reliable forecasting tools.
