AI USE CASE
Sewer Overflow Prediction with ML
Predict sewer overflow events before they happen to protect communities and infrastructure.
What it is
By fusing weather forecasts, real-time flow sensor readings, and infrastructure condition data, machine learning models can predict sewer overflow events 6–24 hours in advance. Early warnings allow operators to pre-emptively activate pumps, divert flows, or alert authorities, reducing overflow incidents by 30–50% in pilot deployments. This lowers environmental fines, emergency response costs, and public health risks. Utilities typically see a return on investment within 12–18 months through avoided penalties and reduced reactive maintenance.
Data you need
Historical flow sensor readings, weather data (historical and forecast), infrastructure condition records, and documented overflow events for model training.
Required systems
- data warehouse
- erp
Why it works
- Dense, well-maintained sensor network providing continuous, high-quality flow and level data.
- Close collaboration between data scientists and experienced network operations staff during model development.
- Automated retraining pipeline that incorporates new overflow events and updated weather inputs regularly.
- Clear escalation and response protocols tied directly to model alert thresholds.
How this goes wrong
- Insufficient or inconsistent sensor coverage across the network leads to unreliable model predictions.
- Rare overflow events create highly imbalanced training data, causing the model to miss critical incidents.
- Lack of integration between the ML alert system and operational response workflows means warnings are ignored or acted upon too slowly.
- Model performance degrades over time if not retrained as infrastructure ages and climate patterns shift.
When NOT to do this
Do not attempt this if your sewer network has fewer than a few dozen flow sensors or if overflow events are too rare (fewer than 10 documented incidents) to train a meaningful predictive model.
Vendors to consider
- Suez Smart Solutionswww.suez.com/en/our-offer/our-activities/water-and-waste-management-services/smart-solutions →
- Xylem Vue (Xylem)www.xylem.com/en-us/innovations/xylem-vue/ →
- Hydroscan (Innovyze / Autodesk)www.autodesk.com/products/innovyze/overview →
- WaPT by Lacroixwww.lacroix-group.com/en/environment/water/ →
Sources
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