In October, A University of Connecticut associate professor will be publishing his research from this past summer, which found that factoring effects from storm debris into tsunami modeling increases the number of buildings predicted to be damaged, according to a UConn Today article. (https://today.uconn.edu/2021/09/uconn-researcher-develops-novel-storm-damage-prediction-model/)
The paper,(https://www.sciencedirect.com/science/article/pii/S0141029621009111) by Associate Professor Wei Zhang alongside Ph.D. students Xiaolong Ma, Xuan Li and Zhixia Ding, modeled a hypothetical tsunami impacting Fairfield Beach, CT and found that the number of buildings predicted to fail in the community increased by 22% after damage caused by debris was considered.
When the model predicted that a building would be washed away, it would forecast that neighboring buildings within a certain range would be damaged by both the tsunami and the debris from the washed-away building, according to the paper.
Accounting for these effects is necessary to design buildings that are better prepared for tsunamis, according to Zhang.
“From a building design perspective, damages are under-estimated since the debris damage from buildings in front of the building is not included in the design,” Zhang said. “To better quantify the possible damages to a community during a tsunami, therefore, it is important to study the moving debris generated from the damaged buildings in the community.”
In addition to studying damage to the entire community, the research also considered the effects on individual buildings in the community, finding that three types of common wood buildings were each predicted to be more damaged when debris was factored into the model.
GIS data of Fairfield Beach was used to choose three building designs representative of those in the community. The researchers used a 1.5 story building from the 1930s, a 1-story 1960s building, and a 2-story 1990s building.
According to Zhang, GIS is a useful tool for visualizing data and creating maps of results.
“GIS majorly provides two important supports to our research and similar research. The first one is to provide integrated data with multiple layers that are associated with individual geographical locations,” Zhang said. “The second one is to provide a better output tool or maps for individuals including researchers or decision-makers to access the research results more easily using maps.”
The authors suggested that further similar research could help to better understand both the damage caused by different types of debris and the movement of debris in water during a tsunami.
Communities are able to better prepare for tsunamis when they have more accurate modeling of potential damage, according to Zhang.
“Accounting for moving debris during a tsunami will help the community better understand the potential risk from a tsunami from the community level other than the potential damages to the individual building. This will also help the community make better plans or preparations to mitigate the possible damages from future tsunamis,” he said.