Pietro De Lellis (Department of Information Technology and Electrical Engineering, University of Naples Federico II, 80125 Naples, Italy) 

Manuel Ruiz Marín (Department of Quantitative Methods, Law and Modern Languages, Technical University of Cartagena, 30201 Cartagena, Murcia, Spain)

Maurizio Porfiri (Center for Urban Science and Progress, Department of Mechanical and Aerospace Engineering, and Department of Biomedical Engineering, New York University Tandon School of Engineering, 11201 Brooklyn, NY, US)

Africa: a continent extremely vulnerable to sea-level rise

Sea-level rise and, more generally, extreme weather due to climate change are challenging the socio-economic development of the continent, as also underlined in a recent report from the World Meteorological Organization. Sea-level rise is expected to have dramatic consequences on the west coast, with the city of Saint-Luis in northern Senegal already experiencing coastal flooding that forced schools, homes, and mosques to be abandoned. Saltwater intrusion is leaving profound marks on agriculture, severely damaging the local economy. Estimating the consequences of such an environmental and economic disaster on migration patterns within and from the continent is vital to enhance our preparedness and ability to cope with it. Toward this goal, it is paramount to i) learn from studies on other geographical areas affected, by similar environmental extremes, and ii) join global efforts to study and mitigate the consequences of sea level rise, which can change the life of more than 600 million people living in coastal regions.

The case of Bangladesh: Sea Level Rise is predicted to affect 1.3 million people by 2050

Bangladesh is a paradigmatic example of a low-income country particularly exposed to the threats posed by environmental change. Sea-level rise poses an immediate threat to Bangladesh, a low-lying country crisscrossed by rivers and plagued by frequent flooding during the summer monsoon season. Its coastline on the Bay of Bengal measures about 580 kilometers (360 miles), with a large portion consumed by the Ganges River delta. Low altitude districts are also those with higher population density, whereby 41 percent of its 163 million people live at elevations lower than 10 meters. The well-being of all of these people living in low-lying coastal regions in Bangladesh is at risk due to sea-level rise. 

Migrants leaving the coast may trigger waves of migration throughout the country

In our recent study, we predict that the cascading effects of the internal migration of people living in low-lying coastal region will ultimately affect 1.3 million people across the country by 2050. We ground our predictions in a mathematical model of human migration that goes beyond mere economic factors to include elements of human behavior—whether people would be unwilling or unable to leave and whether they would later consider returning to their homes. Our model is dynamic in time, whereby it captures when original inhabitants are displaced and how migrants would move to find new opportunities throughout the whole country. Hence, our model predicts cascading effects by reconstructing spatiotemporal patterns of migration.

To ease the quantification of the effect of environmental change, we propose the use of a resilience metric that measures the overall influence of a local shock on internal migration. Through the resilience metric, we unveil a rich, complex landscape of vulnerabilities, with a negative correlation between resilience to a shock at a given district and its local population. According to our predictions, the districts in the south along the Bay of Bengal will be the first to be impacted by sea-level rise, causing a migration that will ripple across the country and affect all of its 64 districts. Some of the envisioned patterns may interact with local economies, causing conflict between migrants and existing residents, triggering further unrest. While the population of the capital, Dhaka, initially will surge, model results suggest that movement away from the inundated capital region may ultimately cause its population to shrink.

Human dimension to economic models

Our new model builds on a previous human migration model that focused on economic migrants in Bangladesh, and it uses the same set of geographic and demographic data. Previous work does not account for return migration or cascading effects, which are key to drive the dynamics of our model.

The previous study predicted that the central region of Bangladesh, including its capital, Dhaka, would receive the largest number of migrants. Our predictions agree with this previous study, but we determine that the ripple effects from that migration could ultimately cause people to leave the capital and its population to decline.

Establishing accurate models to predict human unrest to environmental change is crucial to policy making, offering scientifically backed insight into how resources should be distributed to improve preparedness and potentially mitigate what is unfolding.

Beyond Bangladesh: adapting the approach to different geographical areas

As the model we propose is not data-hungry and it is relatively simple to tune from readily accessible data, we expect that it can be adapted to model migrations dynamics in diverse geopolitical areas, including Europe and Africa. We believe that its predictions can be leveraged to help governments plan and prepare migration policies to mitigate the immediate and long-term impact of sea-level rise, by allocating resources to the most hard-hit regions and ensuring that cities are adequately equipped to deal with the influx of migrants. Our model could be tailored to account for all of these factors, so to increase our preparedness and mitigate cascading effects on global migration patterns within the continent and toward the rest of the world.

Beyond sea-level rise: predicting migrations flows due to environmental perturbations

Although we focused on migrations induced by sea-level rise, our new model can be used to study migration in response to other environmental changes that cause human unrest, such as droughts, earthquakes, or wildfires, and to make reliable predictions based on limited and sparse data. Regardless of the specific source of migrations, our future decisions on this delicate matter should be grounded in mathematical models. Science should provide a toolbox of methods and models for decision-makers, with the ultimate goal of alleviating the socio-political consequences of human unrest. In this context, our model represents a clear step in this direction, which we believe will be followed by a large research effort from a vast and interdisciplinary community of researchers.

[Photo by tarek suman on Unsplash]

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