Disaster Preparedness: How Measurement Science Can Help Your Community

Growing up, I saw the effects of natural disasters on the communities I lived in.

In 2005, several new classmates arrived at my school near Atlanta because Hurricane Katrina had displaced them from their homes in New Orleans.

Just a few years later, I was living in Nashville, Tennessee, when the 2010 floods hit. Nashville got more than 13 inches of rain over two days. It was a scary time, and I was struck by how our community was affected in the aftermath.

Before the flood, one of my friends commuted to school over a bridge, which was about a 10-minute car ride. The flood washed the bridge away. Because there were no other roads in the area, he went from having a short commute to a 45-minute ride. It took years to rebuild that bridge, so my friend - and our whole community - had to adapt in the meantime.

I didn't know it at the time, but there's a term for what I observed as a young student: community resilience. Community resilience is how a community responds to a disaster and builds up its ability to recover from future disasters.

At NIST, we're interested in ensuring that every community is as prepared as possible. Because NIST is a measurement science organization, we want to help everyone plan for resilience in a data-driven way.

In the case of resilience, "community" isn't just your neighborhood. It could be any group of people who have some rules for governing themselves. In my research, I mostly look at county-level resilience. But resilience can apply to college campuses, large employers, apartment buildings, homeowners' associations and more.

So, what does resilience look like in practice?

Let's say a county has an area that's frequently impacted by flooding from a stream. Local leaders consider various options to deal with the flooding. One option would be to restore the stream (cleaning it up and planting trees around it, for example). That stream restoration would reduce the overall flooding, and the community would benefit from the new trees.

How NIST Is Promoting Community Resilience

In an ideal world, every community could afford to take every possible resilience action, but that's not realistic with limited personnel and budgets.

So, as an economist, one of my jobs is to help communities weigh their options when making decisions like this one. We call this resource-constrained decision-making. Economists' role is to help communities weigh alternatives and offer insights into the costs and benefits of each option.

One of the tools NIST offers is Economic Decision Guide Software (EDGe$), a framework for considering different alternatives. It helps decision-makers think through the different resilience options. EDGe$ walks users through the process to do a cost-benefit analysis. So, to go back to the earlier scenario, a community could consider the costs and benefits of how to address flood-prone land.

Our tool is flexible because there's no one-size-fits-all solution for every community. So, everyone can adapt the tool to their needs.

EDGe$ is just one of our efforts here at NIST. We develop a variety of tools and frameworks that help communities increase their ability to withstand (or recover from) disasters.

I love building tools and guidance documents to help communities, especially smaller ones that don't have the budgets to hire consultants. In many cities and towns, there might be one city planner trying to manage disaster resilience among many other responsibilities. So, our goal is to empower these busy people with the tools and information they need to wisely spend their limited budgets.

Community Resilience After Job Losses

Though my early experiences with natural disasters were formative, I became more interested in community resilience in graduate school. At that time, I had the opportunity to study counties in Kentucky, Virginia and West Virginia that had lost a significant number of jobs due to the closing of coal mines. The jobs were relocated to other states.

While you may not think of job losses and natural disasters as being similar, they can actually have some commonalities in terms of impact, such as sudden population loss from people moving away.

During that project, I pored over economic data, examining indicators such as unemployment and median household income. I really hoped I'd find some "silver bullet" that would help communities recover faster from losing thousands of jobs. Unfortunately, I didn't. In fact, my main finding was that the counties that recovered faster were closer geographically to larger metropolitan areas. That's useful information, even if it didn't help the counties that lost jobs and residents.

Of course, that doesn't mean communities cannot take action to recover from mass job loss. While I couldn't solve the problem, this research motivated me to dedicate my career to community resilience.

This experience is one of the reasons why I'm so passionate about building measurement science and decision science tools that governments and residents can apply in their own contexts.

Looking Ahead to a Resilient Future

Unfortunately, disasters will continue to happen, but people are increasingly aware of the need to plan ahead for them.

One way we're working to help with planning is by adding some additional functionality to our tool. One of the additions will help communities value nonmonetary benefits from their resilience plans - for example, the stream restoration scenario mentioned earlier.

It's hard to put a dollar value on how much a community benefits from stream restoration, but that's exactly what we try to do. We want to measure these ancillary benefits, which we call "co-benefits." This helps officials and residents think through their resilience planning and all of the costs and benefits - even ones that are hard to measure. (Measuring hard-to-measure things is what we do here at NIST!)

We're also helping people measure another abstract factor - how risk-averse a community is. We call this "risk preference." It's very challenging to measure a community's risk preference when it comes to natural disasters and other hazards. The decisions are also being made by proxy decision-makers, such as city planners.

This is important research because natural disasters are low-probability but very high-cost events. So, every decision a community makes about preparedness must consider the overall risk preference. While this is a hard measurement challenge to tackle, I am excited to continue working on this project.

In the future, I hope that my research will make the difficult decisions that resilience planners have to make every day a little bit easier - and more data-driven.