hen you think about an earthquake, landslides may not immediately come to mind. But they are a major concern in mountainous regions like the Himalaya where the geology is relatively young and unstable. After a quake, water percolates and loosens the soil, which can trigger massive landslides. Scientists estimate that there were tens of thousands of landslides throughout the Himalayan region in the weeks following the April 2015 quake. Whole villages were buried beneath layers of mud and rock. Hundreds died.
Saxena hoped a new map would help officials think about how to best reduce the risk for landslides, particularly in remote areas. “The first thing is to know if you are in a high-risk zone, and then to decide how to deal with it,” he says.
Back at Yale, Saxena assembled a team consisting of three recent F&ES alums — Ross Bernet
’15 M.E.M., who had specialized in GIS while a master’s student; Angel Herslet
’15 M.E.M.; and David J.X. Gonzalez
’15 M.E.Sc. — and a Yale College undergraduate, Olivia Walker
’16. Jonathan Reuning-Scherer
, a senior lecturer in statistics at F&ES, provided technical support.
They first reviewed the literature to learn how scientists typically assess natural hazards. Building on preliminary data from Deo Raj, they then created a model to identify high-risk areas. Their model incorporated elevation, aspect, slope, roads, population centers, rainfall patterns, and drainage systems. Somewhat surprising, their regression suggested that geologic fault lines are not as important as many other factors in predicting landslides.
The resulting map uses different colors to delineate four hazard classes in Nepal: low, moderate, high, and very high. One can easily see those areas most at risk, and they might not be where you’d think.
While the media tends to favor urban areas, the map suggests these populations are not necessarily at risk for landslides. For example, most of Kathmandu faces a relatively low risk. However, wet, rural areas are highly susceptible. And climate change is exacerbating monsoon patterns throughout the South Asian Peninsula, including Nepal, where current models predict warmer temperatures and increased rainfall. If these models prove to be correct, parts of Nepal could be at even greater risk for earthquake-induced landslides.
Saxena acknowledges that maps such as this can be highly controversial. “Maps can become really politically charged because you can use them to decide whether you’re going to stay in your village or you’re going to move,” he says.
And although it can be tempting to read the map as absolute truth, Bernet cautions that all maps are highly subjective. “We’re trying to tell a story. That’s the point in creating them,” he says. “But what you focus on — the shapes and colors and line thickness — all influence how you read the map. And I think it’s super important as you’re creating a map to remember what people are getting out of it.”
“Our model is 84-percent accurate based on the data we had,” he continues. “We’ve said, ‘Here’s where we found the data, here’s what we’re working with, here’s what we did.’ The hope is that someone who might be using the map to make decisions that affect people’s lives really understands all of that.”