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How can urban stormwater management benefit from artificial intelligence and big data?

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Urban stormwater management is a crucial challenge for many cities, especially in the face of climate change and population growth. It involves planning, designing, and operating systems that collect, treat, and reuse rainwater runoff from roads, buildings, and other impervious surfaces. Traditionally, urban stormwater management relies on conventional infrastructure, such as pipes, drains, and ponds, that often have limited capacity, high maintenance costs, and negative environmental impacts. However, in recent years, there has been a growing interest in applying artificial intelligence (AI) and big data to enhance urban stormwater management and promote green infrastructure.

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1 What is green infrastructure?

Green infrastructure refers to a range of natural or engineered features that mimic or enhance the functions of natural ecosystems, such as infiltration, evaporation, and transpiration. Examples of green infrastructure include rain gardens, green roofs, permeable pavements, bioswales, and wetlands. These features can help reduce the volume and peak flow of stormwater runoff, improve water quality, increase biodiversity, and provide multiple co-benefits, such as urban cooling, carbon sequestration, and aesthetic value.

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Sudipta Pramanik, PhD

Engineer | Researcher | Innovator | Founder
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Rainwater catchment system such as, residential rainwater collection systems/rain barrels can also be helpful to reduce runoff volume and collected water can be used as future resource.

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2 How can AI and big data help?

AI and big data can help urban stormwater management in several ways. First, they can improve the monitoring and modeling of stormwater quantity and quality, by using sensors, satellites, drones, and other sources of data to capture real-time and spatially distributed information. Second, they can optimize the design and operation of green infrastructure, by using machine learning, optimization, and simulation techniques to find the best locations, sizes, and configurations of green features, as well as to adjust their performance according to weather and demand conditions. Third, they can enhance the decision-making and stakeholder engagement processes, by using data visualization, analytics, and communication tools to provide insights, feedback, and recommendations to planners, managers, and residents.

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Sa?a Tomi?, PhD, PE????

30+ Years in Digital Water Helping Utilities Use Models & Data.
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Artificial Intelligence and big data can help enhance urban stormwater management by providing insight into climate change-induced variability. Traditional GI design based on historical rainfall data may not account for the increasing frequency and intensity of extreme weather events. AI, with its predictive analytics and machine learning capabilities, can analyze vast datasets, including real-time weather patterns, to forecast and respond to such events more accurately. This allows for the development of adaptive GI, optimized for current and future conditions, rather than relying solely on past patterns. Consequently, stormwater systems become more resilient and effective in managing the challenges posed by a changing climate.

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Kevin Yue, PE, CEP

Senior Environmental Engineer at Stantec, making the world a better place, one remediation project at a time!
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There is a company that is already utilizing data to help manage stormwater management systems. OptiRTC uses all these tools mentioned above.

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Rob Braman

Waste Approvals Specialist - Environmental Consultant
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Some examples of this feedback would be the design of appropriate "visual graphical dashboards" from large AI analyzed databases for city and community planners to engage in the decision-making process.

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3 What are some examples of AI and big data applications?

There are many examples of AI and big data applications for urban stormwater management around the world. For instance, in Singapore, a smart water management system called ABC Waters uses sensors, cameras, and cloud computing to monitor and control the water levels and quality of more than 200 waterways and reservoirs. In Melbourne, Australia, a green infrastructure mapping tool called Green Infrastructure Potential uses satellite imagery and machine learning to identify and prioritize areas for green infrastructure implementation. In New York, USA, a citizen science project called Smart Citizen Kit uses low-cost sensors and mobile apps to collect and share data on stormwater runoff and green infrastructure performance.

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4 What are some challenges and opportunities?

Despite the potential benefits of AI and big data for urban stormwater management, there are also some challenges and opportunities that need to be addressed. Some of the challenges include the availability, accuracy, and security of data; the integration and interoperability of different data sources and platforms; the ethical and legal implications of data collection and use; the scalability and adaptability of AI models and algorithms; and the social and institutional acceptance and adoption of AI and big data solutions. Some of the opportunities include the development of new skills and capacities for data analysis and interpretation; the creation of new partnerships and collaborations among different stakeholders; the innovation of new business models and services for green infrastructure; and the empowerment of communities and individuals to participate in and benefit from urban stormwater management.

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Raj Subramanian, P.Eng
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I see data collection as the biggest hurdle towards this. Convincing municipalities to invest in data collection and monitoring is the real challenge. Even without AI data availability on traditional or green infrastructure can make a huge difference when we can collect network information. Perhaps the benefits of AI can be used to steer decisions

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5 What are some resources and tips?

If you are interested in learning more about AI and big data for urban stormwater management, here are some resources and tips that might help you. First, you can explore some online courses and webinars that cover topics such as smart water systems, machine learning for environmental engineering, and data science for social good. Second, you can read some publications and reports that showcase best practices, case studies, and lessons learned from different cities and projects. Third, you can join some networks and communities that connect researchers, practitioners, and enthusiasts who share their knowledge, experience, and ideas on AI and big data for urban stormwater management.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Riyad Musa

Former Senior Advisor for the D.G of WHO on Health, Human Environment Protection, and Sustainable Development.
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Thank you for this collaboration. However, this discussion centres mainly on high income countries capable of utilising AI applications. The need for this kind of collaboration is even more applicable to poor country scenarios. Such countries lack water, money, and AI. Hope this can be put in a context that the poor can really utilize and benefit from. Reyad Best regards

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How can urban stormwater management benefit from artificial intelligence and big data?

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3

4

5

6

1 What is green infrastructure?

2 How can AI and big data help?

3 What are some examples of AI and big data applications?

4 What are some challenges and opportunities?

5 What are some resources and tips?

6 Here’s what else to consider

Environmental Engineering

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How can urban stormwater management benefit from artificial intelligence and big data?

1

2

3

4

5

6

1 What is green infrastructure?

2 How can AI and big data help?

3 What are some examples of AI and big data applications?

4 What are some challenges and opportunities?

5 What are some resources and tips?

6 Here’s what else to consider

Environmental Engineering

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