Going on the offensive: How local governments can proactively leverage data against physical climate risk

In June this year, intense rainfall from Tropical Storm Arthur stalled vehicles on Interstate 35, forcing the closure of dozens of arterial roads across Central Texas. Weeks later, a slow-moving convective storm dropped up to 12 inches of rain across southeastern Missouri and the Ohio River Valley, washing out critical roads and triggering localized states of emergency.

These severe, hyper-local flash floods are the kind of weather shocks forcing local governments to rapidly reconsider their data usage. 

For municipal engineers and public sector leaders in emergency management, navigating these compounding crises can feel incredibly taxing — especially when balancing shifting political landscapes, tightening municipal budgets and unpredictable funding cycles.

Yet facing these threats effectively will require a profound shift away from the often-passive data collection of the past. Now, local government agencies have an opportunity to “reverse-engineer” their approach, using geospatial tools to deliver proactive infrastructure resilience. In other words, it’s time to go on the offensive.

Synthesizing Done Right

Data synthesis should derive maximum value from combining datasets, but organizations often overlook the operational engineering pathways between those inputs and a coherent outcome. Public sector teams are doing an incredible job under immense pressure, but without the staffing capacity or time to integrate these tools deeply, data often ends up sitting dormant in silos.

When organizations consistently follow an intentional value chain (data to decisions to actions to outcomes), the results can be startlingly good. However, public organizations still over-index on the “data” aspect of this equation rather than the subsequent steps.

The latest GIS layers and climate projections can buy one operational foresight, but without the operational bridge to translate physical metrics into engineering or emergency workflows, the outcomes that follow will be below par — even within highly data-literate environments.

Here, to help catalyze the desired result among often under-resourced public sector teams, there is an opportunity to “reverse engineer” the inputs from the outcomes. To achieve this effectively, local government data experts must precisely define what they want out of the data and can enable these outcomes using the following three A’s of data:

• Accuracy: Do we need sub-ft accuracy for a specific culvert design, or a broader regional model for high-level risk screening?
• Availability: Do we look at historical averages, or do we need forward-looking climate projections for 2050 to protect long-term assets?
• Accessibility: Can an emergency responder access insights on a tablet mid-storm or does it require a GIS specialist to interpret?

Best practice shows that digital transformation is an equal construct of People, Process, Data and Tools. By “beginning with the end in mind”, data can be leveraged with purpose from the start, resulting in better outcomes.

Data Screening For Better Decisions

Despite the wealth of advanced Geospatial data systems available, different municipal departments can still retreat into isolated data silos, leaving other teams with zero contextual insight or a distorted view of the data. 

On the other hand, over-sharing of highly dense complex data without proper guidance on effective use cases is just as common and can lead to analysis paralysis which stymies organizational cohesion.

Our recent work with a U.S. state agency demonstrated best practice by creating a simple three-column guidance framework: Approved use case; use with caution/guidance; and do not use.

This simple investment in the “People” side of digital (making life easier for the public sector workers running these systems daily) boosted analytic capabilities more than any algorithm, simply by improving confidence in decision-making and investing in strategic counsel only where it was required. Here is how that framework looked in practice:

Contextualizing One-Off Extremes

Identifying rare, extreme weather events is a complex task requiring massive climate simulations. In balancing in-house capabilities with specialized external partners, local agencies must invest in identifying where their greatest data and analytical gaps lie.

Risk is a combination of likelihood and impact with data gaps existing on both sides. Public sector organizations must ask whether these gaps lie in their own domain, where they have unique expertise, or outside, where external specialists are better equipped; for example, identifying extreme flood risk across a vital municipal network.

• Likelihood: Trajectory and early identification are part of a meteorological challenge, large parts of which the local authority has no reason to try to tackle; it is a primary force of nature, and being tackled by domain experts globally who have more funding, expertise and motivation to solve. Trying to build these massive climate models in-house drains valuable local budget away from front-line community safety.

• Impact: If hurricane X strikes at location Y at time Z, what will be the impact? This is the engineering challenge which requires both domain understanding of local public works operations, as well as domain understanding of extreme weather. This is where local government shines; your internal teams possess the invaluable local context needed to map physical hazards directly onto community vulnerabilities.

Typically, internal initiatives fall apart when an organization tries to operate outside of their domain, hemorrhaging time and funds in solving problems they are not best placed to solve. By leveraging industry-vetted hazard data from specialized partners, local agencies can focus 100% of their energy on impact planning and protecting local communities.

A New Pathway For Resilient Infrastructure Design

Resilient infrastructure can be incrementally "upgraded" to improve its performance over its lifespan. This approach is built on the "Adaptation Pathways" concept, which is fast becoming a global standard for resilient design.

Rather than a fixed set of design performance standards, a series of potential future performance criteria are set, against which an asset — like a municipal stormwater network—must be able to be modified to perform in the future under potentially different weather extremes. This logic can be applied to building for today's climate, while ensuring the system can be easily upgraded to handle heavier rainfall in 20 years.

Skillfully balancing capital spending against the protection gap is the only realistic way forward. We cannot rely on a single generation of funding to build massive, static defenses for every future extreme, nor can we blindly build only for today's imminent climate threats. In a dynamic political landscape where public budgets are heavily scrutinized, presenting a clear, phased roadmap for incremental upgrades is how local teams protect vulnerable communities and manage capital in equal measure.

Conclusion

Infrastructure resilience isn't about unlimited budgets; it is about reclaiming organizational agency. Public sector employees have endured years of being sidelined, underfunded and politically targeted, but local teams are the true first line of defense. 

By connecting 50-year adaptation pathways to their daily landscape of people, process, tools and data, public sector professionals can go on the offensive — proving they can do on a dime what critics claim requires a dollar.

Ultimately, the goal is not to turn overstretched local agencies into climate modeling labs. By utilizing specialized external datasets for the heavy computational lift, public sector leaders can protect their capacity and focus entirely on what they do best: using unmatched local expertise to make bold, proactive decisions. It is time to stop playing defense. Armed with the right tools, local officials can — and will — lead the charge on climate resilience.

Peter Slater is an engineering business development manager at Fathom.