[Note: this post part of a series that describes the Columbia Global Flood Initiative, a new Earth Institute initiative that attempts to better understand, predict and mitigate the impact of extreme floods around the world. For more information about the project, please see our website at the Columbia Water Center].
As I write this, the United States Army corps of Engineers is preparing to blow up levees on the Ohio River near Bird’s Point Missouri in order to save the town of Cairo, Illinois, as the river rises and rain continues to drench the region. Cairo is downstream from the place where the Ohio and Mississippi Rivers meet.
The move comes only a day after the U.S. Supreme Court refused to hear an appeal from the state of Missouri, which had sued to stop the intervention. Missouri officials contend that blowing up the Bird’s Point levees would destroy 100 homes and inundate some 130,000 acres of Missouri farmland.
Cairo, meanwhile, is a poor town of about 3,000 residents, 75 percent of whom have already evacuated. If the Cairo levees burst, the town could be covered in 15 feet of water. Officials are now going door to door to convince remaining residents to leave.
It is a story that highlights the tragic dilemma water managers must frequently face; given the stakes, it should not surprise us when such issues become contentious and painful.
The question is, in an era of increasing flood risk, can we do a better job of understanding, predicting and preparing for these kinds of events?
As it happens, Columbia climate and hydrology scientists have been looking at the pattern of flooding on the Ohio River for some time. A composite of 17 major Ohio River flood events at different times shows how major floods follow a very consistent pattern of moisture flow.
This structure gives us a strong suggestion that the possibility of extreme floods for the Ohio River could be predicted—days, weeks or even a season ahead. Such a prediction would clearly give emergency responders more time to develop action plans, give governments more time to coordinate and develop policy responses. Perhaps most importantly, it could give water managers better decision support systems to proactively manage water releases and allocation—and potentially avoid the need to make such painful tradeoffs.