Harnessing data: the future of stormwater management

June 28, 2024
Utilizing the latest tools and software, stormwater professionals can use predictive modeling to forecast pollution and flooding.

In an era of increasing urbanization and climate uncertainty, stormwater management faces unprecedented challenges. Leveraging the latest in data-driven technology, stormwater professionals can now turn the tide on flooding and pollution with precision and foresight.

Minimize failure risks with real-time data integration

Having the latest data on hand to characterize the condition of stormwater conveyance networks allows identification of vulnerable areas and potential flooding hotspots. Integrating Geographic Information Systems (GIS) data on stormwater infrastructure, such as pipes, channels, culverts and outfalls, with data from field crew operations can provide critical status updates. Recent inspections and maintenance data can provide alerts for potential conveyance and treatment network failure points in near real time. These insights translate to reducing the risks associated with the failure of stormwater conveyance and treatment.

For example, knowing the locations of inlets and catch basins that sporadically clog up can prompt the dispatch of maintenance crews to those areas before storms. Likewise, having the data to quantify the likelihood of infrastructure failure based on age, material or inspections can inform the need for pre-emptive actions to shore up weak points. These insights depend on having the technical capability to rapidly turn field observations into actionable intelligence. That means adopting mobile apps for field data collection, a GIS-based platform as a central data hub, and cloud data storage so that outputs can be accessed wherever they are needed.

Discover new opportunities with advanced simulation

Simulation models are used to predict stormwater behavior under various scenarios to inform flood protection, watershed-scale planning, and infrastructure design. They can also help identify opportunities for stormwater infiltration, treatment, and capture. Combining well-tested modeling approaches with cloud-based processing generates some truly impressive outputs. It is now possible to produce high resolution (30m) stormwater runoff predictions for entire cities, watersheds, and regions. For example, in partnership with 2NDNATURE, the Pacific Institute quantified the stormwater runoff capture potential in urbanized areas across the entire United States4. The resulting estimates can be quickly updated to reflect the growth of cities and shifting rainfall patterns. Such tools remove many of the barriers to accessing model outputs for non-expert users. They can also help facilitate a shift of perspective to view stormwater not just as a problem, but also as a valuable resource for augmenting municipal water supplies.

Ready to revolutionize stormwater management? 

Transforming a stormwater program to continually rely on the latest and greatest data is a marathon, not a sprint. Everyone starts at a different level of data readiness and technology adoption. Like preparing for a marathon, the starting point matters much less than deciding to begin the training. Here are a few simple tips that can help any program get going:

Dive into your stormwater data

Data gaps create barriers to progress. Do you know where all your control measures are located? How about data from field crews? Control measure and maintenance tracking data that are siloed off from other stormwater program data are less useful for prioritizing actions.

Evaluate your current technical level

There are likely more efficient and accurate ways to capture, store and analyze your data. An honest assessment of current technical capabilities and where they fall short of generating useful insights is a good place to start.

Learn from others further along the path

While every stormwater program is different, many lessons are transferable. Engaging at conferences, workshops and webinars are good ways to learn about how the technologies used by other programs are evolving and pitfalls to avoid.

Start simply

A full digital information overhaul can feel daunting. Start by identifying a type of data that would improve a specific decision or task. Is the problem that the data are not captured, or is there a technical barrier preventing access or interpretation?

Conclusion

Embracing data-driven strategies and modern technologies is not just a trend — it is a necessity for future-ready stormwater management. The use of GIS-centered tools that run in the cloud and can be rapidly updated through mobile apps are the way to ensure that planning aligns with on-the-ground priorities. By investing in these tools, communities can reduce risks, optimize resources, communicate the value of investments and play a central role in building more climate resilient communities across the US.

References

  1. Schlaudt, E., and J. Klein. "The Clean Watersheds Needs Survey and Stormwater Needs." In Stormwater Summitt 2021. Water Environment Federation, 2021.
  2. Nodine, Tyler G., Gary Conley, Catherine A. Riihimaki, Craig Holland, and Nicole G. Beck. "Modeling the impact of future rainfall changes on the effectiveness of urban stormwater control measures." Scientific Reports14, no. 1 (2024): 4082.
  3. Conley, Gary, Robert I. McDonald, Tyler Nodine, Teresa Chapman, Craig Holland, Christopher Hawkins, and Nicole Beck. "Assessing the influence of urban greenness and green stormwater infrastructure on hydrology from satellite remote sensing." Science of the Total Environment817 (2022): 152723.
  4. Berhanu, Bruk, Morgan Shimabuku, Shannon Spurlock, Jessica Dery, Heather Cooley, Catherine Riihimaki, Nicole Beck, and Gary Conley. 2024. “Untapped Potential: An Assessment of Urban Stormwater Runoff Potential in the United States” Oakland, Calif.: Pacific Institute.
About the Author

Gary Conley

Gary Conley is Chief Scientist at 2NDNATURE and has spent the last 20 years tackling water pollution problems. He leads scientific development of software tools that turn streams of data into actionable knowledge, improve watershed stewardship, and reduce the cost of clean water for cities across the US.