Harnessing sewer data: Shaping the future of urban flood modelling
As extreme weather events become more frequent and urban landscapes grow more complex, flood modeling has never been more critical. This latest session of the Autodesk Water Webinar Series, co-hosted by Smart Water Magazine, titled: 'How sewer network data can impact urban flood modelling,' explored how leveraging high-quality sewer network data is revolutionizing urban flood resilience. Beyond just technical discussions, the session emphasized how cutting-edge technologies are shaping the future of flood modeling and real-time water management.
Expert insights: The role of data quality in predictive flood modelling
Featuring Paolo Tamagnone, flood modeller and scientist at RSS-Hydro, and Caryn Novak, Civil and Environmental Engineer at Autodesk Water, the webinar showcased the critical importance of data quality and completeness in flood risk assessments. The speakers explored how sewer network datasets impact predictive modeling, outlining the consequences of missing or outdated infrastructure data, which can severely distort model accuracy. They also pointed out that inconsistent formats from different agencies create integration hurdles, complicating flood simulations.
Paolo Tamagnone’s presentation focused on his case study in Differdange (Luxembourg), where he assessed the influence of sewer network data completeness on 2D/1D flood models. His research demonstrated that even with up to 50% missing drainage network data, reliable flood predictions could still be obtained for extreme rainfall events. However, he emphasized that neglecting key elements such as main collectors or surface inlets led to substantial errors in flood extent estimations.
Autodesk's portfolio supports decision-making by integrating various data sources, including GIS-based hydrological mapping and 2D/1D hydraulic modeling
The study incorporated high-resolution LiDAR data, detailed land use classifications, and updated cadastral information to refine the model. Calibration was performed using reported flood events, given the absence of real-time sensor data in the study locations. The research also tested various levels of sewer network completeness to understand their impact on model performance, revealing that surface flow played a greater role in areas with insufficient underground drainage representation.
Caryn Novak complemented this discussion by presenting Autodesk’s InfoWorks ICM as an advanced integrated catchment modeling solution. She highlighted how this technology enables dynamic simulations of flood risk, offering municipalities a way to plan for extreme weather, optimize infrastructure investments, and reduce downtime. Autodesk's portfolio supports decision-making by integrating various data sources, including GIS-based hydrological mapping and 2D/1D hydraulic modeling.
Real-world applications: Case study from Luxembourg
To illustrate the significance of data quality, Tamagnone presented his study on Differdange, Luxembourg:
- Differdange, Luxembourg – This study assessed how different levels of sewer network completeness influenced the accuracy of 2D/1D coupled flood models. The research found that even small gaps in pipe connectivity data could significantly alter flood predictions, reinforcing the need for well-maintained datasets. The study incorporated high-resolution LiDAR data, land use classifications, and cadastral information to refine the model.
Tamagnone also discussed how model performance was affected by varying degrees of network completeness. The results highlighted that while simplified models could still provide useful insights, omitting key infrastructure elements like inlets and main collectors led to notable discrepancies in flood extent predictions.
Engaging discussions: Audience questions and expert answers
The Q&A session was highly interactive, with attendees raising technical questions about the study and its applications. Some of the key questions addressed included:
- How does the completeness of sewer network data impact flood modeling accuracy? Tamagnone explained that while simplified models can still provide meaningful predictions, neglecting key components such as main collectors leads to significant underestimations of flood risks.
- How were model results validated given the lack of real-time sensor data? The discussion clarified that the model was calibrated using reported flood incidents from authorities and past documented events, rather than direct sensor observations.
- What are the main limitations of the study's approach? Tamagnone acknowledged that while high-resolution datasets improve accuracy, access to up-to-date cadastral and network information remains a challenge in many urban areas.
- How can blue, green, and gray water be segregated at the source while considering future demand and supply, as well as flood forecasting for sustainability? The discussion touched upon the importance of integrating water management solutions with urban planning to optimize resource allocation and resilience.
- How can the model be adapted to extreme flood events, like those experienced in Valencia, Spain? Tamagnone highlighted that model adaptability depends on having a well-represented drainage network and the ability to simulate both underground and surface flow dynamics effectively.
- What is the best practice when receiving as-built data from various sources and new topographic data in different datums due to different agency interfaces? Experts emphasized the need for standardized data integration methods and automated transformation tools to improve consistency in flood model inputs.
The high level of audience engagement was a testament to the growing relevance of these topics.
Looking ahead: The future of flood modeling with Autodesk
The webinar reinforced the urgent need for accurate and well-integrated sewer network data in urban flood resilience planning. With AI-driven automation, GIS integration, and advanced multi-source validation, flood modeling is entering a new era of precision and predictive capability.
Paolo Tamagnone concluded by emphasizing that while complete network information is ideal, accurate flood modeling is still achievable with strategic simplifications. Key takeaways included the importance of representing main collectors and surface inlets accurately and leveraging high-resolution urban datasets to compensate for missing sewer data. He also stressed the need for continued research on refining flood models to account for real-world infrastructure variability.
The discussion also made it clear that the future of urban flood management depends on a combination of technological innovation, cross-agency collaboration, and a commitment to high-quality data collection. Autodesk and Smart Water Magazine will continue this conversation in the coming months, analyzing the challenges and opportunities of digitalization in water management.