Researchers from Indiana University have made significant strides in understanding the phenomenon of “river avulsion,” offering a new predictive framework for when and where rivers might suddenly change course. This breakthrough, has profound implications for managing flood risks, particularly as climate change exacerbates global water cycles and human expansion into flood-prone areas continues. Led by Ph.D. student James “Jake” Gearon from the Department of Earth and Atmospheric Sciences at Indiana University Bloomington, the research team utilized cutting-edge satellite technology, specifically lidar, to map how certain landscape features contribute to the occurrence of river avulsions.
These events happen when sediment builds up in a riverbed, causing the river to spill over its banks and carve a new path, often with devastating consequences. For instance, the 2008 avulsion of the Kosi River in northern India directly affected over 30 million people and caused over $1 billion in damages. Analyzing data from 174 river basins around the world, the researchers found that these events are more likely to occur near mountain ranges and coastal areas, where rapid more sediment. It was found that 74% of the variants were close to these characteristics. Their research presents a model for mapping “pathways,” and potential ways rivers can diverge from their current course. This tool can help governments and planners, especially in areas with limited flood control infrastructure, to identify areas of risk. In the past, scientists believed that the differences were caused by a higher river or a steeper path for the water. This study shows that both factors work together, with different influences depending on the river’s location. The findings highlight the inadequacy of current flood models, which focus on rising water levels from rainfall and fail to account for the sudden and unpredictable nature of avulsions. The implications are particularly critical for the Global South, where river avulsions often lead to significant human and economic losses. The team’s predictive model, requiring minimal data, could prove essential for preparing and mitigating future avulsion-related disasters, offering a much-needed tool for regions at high risk.