Moving from alarm points to catchment intelligence
Often wastewater teams start with sewer level monitoring because they need to solve one problem: overflows.
Sensors are installed at high-risk sites, alarm thresholds are configured, when levels approach surcharge operators are notified and crews respond. It reduces environmental risk, supports compliance and improves response times. Win win.
But if that’s all they’re looking at it is leaving significant value on the table.
When sewer level monitoring is viewed only as an alarm system, each sensor is treated as an isolated asset. In reality, every monitored asset sits inside a hydraulic network. When it rains, the network responds as a system. And that response can be a treasure trove of information.
With the right deployment strategy, level sensors can become a powerful I&I mapping tool.
From site monitoring to catchment behavior
Inflow & infiltration rarely present as one single dramatic failure. They can be very hard to pinpoint. But they can appear as patterns.
Things like:
- A sub catchment that responds weirdly to moderate rain
- A zone that takes longer to recover after storms
- A steady rise in dry-weather baseline levels over months
- Frequent minor surcharge events that never quite reach overflow
These behaviours can easily go unnoticed when the focus is on surcharge alarm management. However, when sensors are deployed across a catchment the data begins to reveal comparative hydraulic performance.
So the shift can go from ‘did the site overflow?’, to ‘how did the catchment area behave compared to elsewhere?
It’s sewer level monitoring moving from reactive protection to system intelligence.
Sewere level monitor installed in a riser.
Building a catchment performance map
Creating a catchment performance map doesn’t need advanced hydraulic modelling from day one. It begins with consistent level monitoring across representative sub-catchments and correlation with rainfall data.
Wastewater teams can extract significant insights be focusing on 5 behavioural indicators:
- Dry-weather baseline levels. Stable levels provide a reference. Gradual increases could mean sediment build-up, partial blockage or infiltration.
- Rise rate during rain. Rapid level increases in response to relative low rainfall often signal high inflow pathways.
- Peak depth relative to pipe capacity. Comparing peak levels across similar pipe sizes and slopes helps identify disproportionately stressed zones.
- Recovery after rain ends. Slow drawdown can indicate downstream restrictions or limited hydraulic capacity.
- Year-on-year trend drift. Comparing event responses over seasons can show whether performance is deteriorating.
When you look at all these factors across multiple monitored locations, patterns start to emerge. The areas that are performing poorly start to stand out. The network begins to tell its story.
Why this matters for I&I programs
Ok, so what if you can see the patterns in the network, why does this matter?
I&I mitigation programs are expensive. Lining, rehab, upsizing, root removal all require significant funding. Utilities must prioritize carefully and justify the decisions.
Actual detection of I&I relies on CCTV inspections, smoke tests and flow isolation studies. They’re cumbersome tests that can’t just be done willy nilly. Quantitative evidence of rainfall response behaviour allows utilities to rank sub-catchments by hydraulic stress.
This allows:
- Data-driven prioritization of I&I investigation zones
- Clear pre- and post-intervention comparison
- Evidence-based funding submissions
- Improved regulatory reporting
Instead of stating that an area "appears problematic", utilities can demonstrate that a specific catchment responds 40 per cent more aggressively to equivalent rainfall than other areas.
That level of clarity strengthens the business case considerably.
Practical takeaways for wastewater utilities
For utilities considering expanding or refining sewer monitoring programs, there are a few steps that can maximize long-term value:
- Deploy in clusters. Monitoring a single high-risk site ticks the box for overflow prevention, but provides limited system insight. Monitoring across a sub-catchment enables comparison.
- Always correlate with rainfall data. Level data without rainfall context limits interpretation. Rainfall intensity and duration provide essential reference points.
- Don’t just look at the peaks. Recovery curves are just as important. The speed at which a catchment drains often reveals more about capacity and restriction than the peak depth.
- Track baseline drift overtime. Long-term dry-weather trends can signal emerging structural or infiltration issues.
- Use monitoring data to validate capital outcomes. Before and after comparisons strengthen the case for rehab effectiveness.
From monitoring to intelligence
Sewer networks are dynamic systems. Rainfall, groundwater interaction, asset condition and blockages all shape hydraulic behaviour.
Distributed sewer level monitoring allows utilities to see that behaviour clearly.
When viewed through a catchment lens rather than an alarm lens, each sensor becomes a data node in a wider performance map. Over time, that map becomes one of the most valuable planning tools available to wastewater operators.
The opportunity is not just to prevent the next overflow.
It is to understand the network well enough to prevent the next decade of them.
To get started on your I&I journey get in touch with the team at Kallipr.
