This summer, CEE Assistant Professor Sabine Loos led a team of students and collaborators from the Center for Social Solutions (CSS) in conducting an in-depth study in Nepal’s Chitwan Valley as part of a pilot grant funded by the Institute for Social Research (ISR) and the College of Engineering. The project sought to blend engineering…
This summer, CEE Assistant Professor Sabine Loos led a team of students and collaborators from the Center for Social Solutions (CSS) in conducting an in-depth study in Nepal’s Chitwan Valley as part of a pilot grant funded by the Institute for Social Research (ISR) and the College of Engineering. The project sought to blend engineering and social science methods to better understand the history and impact of flooding in this region over the past two decades.
The ISR has been collecting household data in this region since 1994 as part of the Chitwan Valley Family Study. However, data on flood experiences had not been systematically collected. This project’s research aimed to fill that gap by collecting historical flood data from the past 20 years to link with the ISR’s existing household data. Loos and her team’s research seeks to identify the areas and families within the Chitwan Valley that are most affected by flooding and explore how extreme flood events can impact households. To do so, Loos and her team conducted exploratory interviews, speaking with Chitwan Valley residents and exploring the landscape to identify locations of previous floods.
“We conducted exploratory interviews and were given tours around the Chitwan area so we could explore the neighborhoods that had been flooded in the past,” Loos said. “We then got to speak with a few residents who’ve been living in this area and hear some of their experiences with flooding.” Collecting this qualitative, experiential data from residents will help Loos and her team paint a clearer picture of the environmental history of the Chitwan Valley.
The team also plans to conduct formal focus groups in order to create a more comprehensive timeline of flooding events in the area — something that, with little to no quantitative flooding data, the Chitwan Valley and its residents are sorely lacking.
“It’s called the Neighborhood History Calendar method,” Loos explained. “It allows you to establish a timeline which can then be used to determine when other significant events happened. Because we don’t have the type of data that you would get from flood sensors, we need to get more qualitative and locally based experiences, which we can then combine with remote sensing data.”
Looking ahead, the research team plans to combine their qualitative findings with remote sensing data and any available ground sensor data to create comprehensive flood maps. This will help them understand the impact of flooding on Chitwan Valley households and families.
“We’re going to work with the ISR to connect our data with their longitudinal household data set,’” Loos explained. “This will help us identify which houses or families are affected most and provide us with data on how flooding has affected family decisions. We’ll be trying everything to see if there’s any associations between the flooding and the household impacts, from impacts on health to livelihoods and migration.”
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