C+S March 2022 Vol. 8 Issue 3 (web)

With this in mind, Eby and the First Street Foundation put together a team of around 80 people to begin building a model for the consequen- tial risks of flooding due to climate change. This report, titled “the 4th National Risk Assessment: Climbing Commercial Closures”, builds on previous research by the First Street Foundation, analyzing how flood - ing financially impacts 1-4 unit residential properties. This is done by evaluating annualized average losses associated with flooding for retail, office, and multi-unit residential properties. According to Eby, this team was composed of top academic experts from each different area or kind of flooding. By gathering experts in different kinds of flooding such as hurricane flooding, sea level rise flooding, etc, Eby and his team used a com - prehensive view of flooding to “build out implications” by looking at residential properties. This means that this comprehensive model not only tells the likelihood of water reaching the building, but also how high that water will be and whether or not it will be able to enter the structure. From there, Eby and his team used depth damage curves from the U.S. Army Corps of Engineers to understand how a home will be impacted from a cost function. These depth damage curves are developed using data collected from mostly residential properties that have been impacted by flooding. This data is then aggregated to give an approximate relationship between the level of flooding and the financial impact that comes from it. After completing models for residential properties, the team needed to perform the same analysis for commercial properties as well. While residential flooding can have a massive financial impact, the same is doubly true for commercial properties. The flooding and subsequent damage of a commercial property or a commercial center requires money to clean and fix any structural damage, but it also prevents that business or commerce center from earning money during the flood - ing and repair processes. However, Eby points out that, while most residential properties are built in mostly the same way, the same is not true for commercial properties, which are more unique based on square footage and property use. To get a better grasp of how commercial properties are built and their structural elements, the First Street Foundation partnered with Arup, who have nearly seven decades of experience working with commer- cial properties. The team at First Street Foundation utilized Arup’s domain expertise to give a better understanding of what happens to these commercial structures when water gets in. Eby says that this partnership combined First Street Foundation’s flood modeling and data with Arup’s experience, allowing them to more accurately predict the damage once water does get into the building. Arup’s first challenge, according to Arup's San Francisco Resilience Leader Ibbi Almufti, was to address the limitations of the depth dam- age curves, which were developed using data from primarily residen- tial buildings and didn’t meaningfully take into account things like building height. Almufti and his team couldn’t rely on a data-driven approach due to a lack of data, so the team relied on a “first principles of engineering” approach. In other words, Almufti and his team were trying to understand what comprises these types of buildings, what’s inside them, and what would happen to the specific components of

them when touched by floodwater. By taking into account the damage from floodwater to these individual components, this approach encom - passes the financial cost for their repair. To create this new model using the “first principles of engineering” approach, the teams had to first create several different building ar - chetypes. With nearly 3.6 million commercial properties throughout the United States, it was imperative that these be categorized into smaller units. For example, one of these archetypes was a low-rise timber building with a basement. There ultimately ended up being 30 building archetypes that were used in the report. Once these arche- types were established, the next step was to populate these buildings with data such as square footage of flooring and type as well as linear feet of piping and others by working with cost estimators. This pro- cess also utilized mechanical engineers to input information like type and location of equipment. According to Almufti, this information is compiled into what is known as an exposure model for the different building archetypes. Almufti notes that, once these archetypes were established and the ex- posure models were populated, the process of combining it with First Street Foundation’s analysis was intuitive. Using First Street Founda - tion’s model, any point of flooding can be measured in feet and mapped onto what components would be exposed to the floodwaters. From here, Arup’s engineers developed fragility curves for each of the com- ponents–partitions, flooring, equipment, etc.–that could be affected by floodwater. These fragility curves relate flood depth to the probability that a particular component would be damaged to a certain extent. This allows them to not only estimate the damage of a flood to a structure, but also repair actions. Eby believes that this report gives property owners and communities power in the form of knowledge. Eby and Almufti both point out that such knowledge is especially important for communities that have not historically been at risk for flooding but, because of climate change, need to begin preparing for the possibility of an increase in flood events. They also believe that the information in the report helps property owners tackle “low-hanging fruit” when it comes to preparing for future flooding events, helping places like industrial parks think about where their critical equipment is stored and how its likely it is to be damaged.

LUKE CAROTHERS is the Editor for Civil + Structural Engineer Media. If you want us to cover your project or want to feature your own article, he can be reached at lcarothers@zweiggroup.com.


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