Event Duration Monitoring (EDM) Sensors: Best 7-Step Plan
Sewer pollution and storm overflow performance are no longer “back-office” topics. They sit in the spotlight for regulators, communities, and operational teams who need faster response, better evidence, and clearer prioritisation of interventions. At the same time, water quality expectations are rising across catchments, treatment works, and distribution networks — where continuous monitoring is increasingly favoured over occasional sampling.
This is why search demand is growing for Section 82 water quality compliance, real-time CSO overflow alerts, and utility-grade sensor terms such as NB-IoT turbidity sensor, self-cleaning pH probes for utilities, and DWI compliant water quality monitoring.
This guide is written for UK water companies, councils, framework contractors, and asset operators who want a monitoring programme that is practical, defensible, and operationally useful — not just a dashboard.
Image (place after this intro): a chamber install / sensor in a manhole
Alt text: Event Duration Monitoring (EDM) sensors installed for real-time CSO overflow alerts
Why storm overflow monitoring is changing in the UK
Storm overflows are now expected to be evidenced, not explained away. That means fewer assumptions, fewer “we think it happened around…”, and more time-stamped truth: what occurred, how long it ran, and how your response unfolded. For many organisations, the immediate driver is improved overflow reporting and actionability; for others, it’s the need to demonstrate clear governance and risk reduction in sensitive catchments.
If you want AQUAIOT context while reading:
https://aquaiot.co.uk/service/sewer-monitoring/
External reference (storm overflow policy/guidance):
https://www.gov.uk/government/publications/storm-overflows-policy-and-guidance/storm-overflows-policy-and-guidance
Event Duration Monitoring (EDM) sensors: what to measure at CSOs
Event monitoring works best when it supports decisions, not just compliance reporting. In practical terms, an EDM deployment should help you answer questions like:
- Which assets are persistently active (and therefore likely candidates for targeted intervention)?
- Which assets are seasonal or rainfall-driven (and therefore need different operational logic)?
- Which events correlate with known blockage corridors, capacity issues, or pump constraints?
- Which assets generate repeat incidents because alerts are late, unclear, or unactioned?
A well-configured approach focuses on reliability, timestamp accuracy, and operational usability. It should also create an evidence base that can be aligned with receiving-water monitoring, so you can move beyond “it spilled” to “what happened next”.
AQUAIOT sewer monitoring overview:
https://aquaiot.co.uk/service/sewer-monitoring/
How to specify Event Duration Monitoring (EDM) sensors in procurement
When buyers say “we need Event Duration Monitoring (EDM) sensors”, what they often mean (or should mean) is: “we need consistent event evidence, robust uptime, and a clean audit trail”.
A procurement-ready specification usually covers:
- Asset identification (clear naming, location accuracy, and consistent mapping to your asset register)
- Comms uptime targets (and what counts as acceptable data gaps)
- Battery/service expectations (realistic intervals, not brochure figures)
- Alert routing (who receives what, when, with acknowledgement)
- Data exports (so reporting does not become a manual spreadsheet exercise)
- Governance controls (access, changes, and retention)
If you’re working within frameworks, include the operational workflow early — because alerting that doesn’t match duty patterns or contractor SLAs will quietly fail, even if the sensors are technically “working”.
Section 82 water quality compliance: building receiving-water evidence
EDM gives you event truth at the asset. Section 82 water quality compliance moves you towards evidence in the receiving water — typically by monitoring upstream and downstream locations to establish baseline conditions and detect change during events.
This matters because the “impact story” is rarely explained by one metric. You want to understand whether changes are repeatable, whether they persist after events, and whether they correlate to discharge timing, rainfall, and catchment behaviour.
Legislation reference (Section 82):
https://www.legislation.gov.uk/ukpga/2021/30/section/82
Image (place here): upstream/downstream river monitoring point
Alt text: Section 82 water quality compliance monitoring upstream and downstream of storm overflows
A useful internal supporting guide for catchment-style monitoring:
https://aquaiot.co.uk/blog-river-monitoring-uk-continuous-water-quality/
Real-time CSO overflow alerts: from monitoring to prevention
A portal full of charts is not a response plan. The value shows up when monitoring reduces incident duration, improves time-to-investigate, and prevents repeat occurrences.
Real-time CSO overflow alerts should be designed as an operational workflow:
- Thresholds calibrated to site reality (so teams trust the alerts)
- Escalation routes aligned to duty cover and contractor SLAs
- Acknowledgement tracking (so alerts have ownership)
- Context included in the message (asset, trend, comms/battery state, and any supporting signals)
- A simple “first actions” checklist (so response doesn’t depend on who is on shift)
This approach reduces “alarm fatigue” and improves response consistency. It also strengthens governance: you can show what triggered the alert, who acknowledged it, and what actions followed.
If you want to connect alerts to wider water quality outcomes, pair alerts with receiving-water monitoring at the right locations rather than trying to instrument everything at once.
Where to deploy first: a defensible prioritisation model
A practical prioritisation model helps you defend spend, deliver quick wins, and avoid instrumenting low-value sites first. A common tier approach looks like this:
Tier 1: sensitive receptors and high-profile locations
Bathing waters, chalk streams, SSSIs, repeat complaint zones, politically sensitive catchments.
Tier 2: repeat spill performers and known high-risk assets
Assets with persistent event history, known capacity constraints, or frequent operational issues.
Tier 3: blockage and pollution corridors
FOG-risk areas, low-gradient networks, older combined sewers, known debris hotspots.
Tier 4: catchment context stations
Upstream/downstream river stations plus supporting context (where relevant) to interpret event signatures.
The key is not “maximum coverage”; it’s “maximum operational value per instrumented site” — and a clear path to scaling once you’ve proven your baseline.
Water quality standards: NB-IoT turbidity sensor and self-cleaning pH probes for utilities
Water quality monitoring is not only about rivers. Utilities are increasingly deploying continuous monitoring across treatment and distribution, where the business case is faster detection, stronger assurance, and reduced manual sampling burden.
This is why specifications increasingly include terms like:
- NB-IoT turbidity sensor
- Self-cleaning pH probes for utilities
- DWI compliant water quality monitoring
Turbidity is often one of the fastest indicators of disturbance. In treatment and distribution contexts it can flag process issues, intrusion risk, or unusual events that justify rapid investigation. In receiving waters, it can help detect event-related changes when interpreted with upstream/downstream placement and event timing.
pH is critical for process control and corrosion risk, but it is vulnerable to fouling and drift in real-world deployments. Self-cleaning designs (for example, anti-fouling features or wiper mechanisms) can reduce maintenance burden, stabilise readings, and improve trust in alarms — which is essential if you want teams to act on the data.
AQUAIOT water quality service:
https://aquaiot.co.uk/service/water-quality-monitoring-uk/
Image (place here): compact multi-parameter station or probe set
Alt text: NB-IoT turbidity sensor and self-cleaning pH probes for utilities for DWI compliant water quality monitoring
Helpful internal reference on parameter selection:
https://aquaiot.co.uk/water-quality-parameters-uk/
DWI compliant water quality monitoring: what “compliance-ready” looks like
“Compliance-ready” monitoring is about governance and assurance, not just sensors. For a DWI-aligned mindset, you typically need:
- Calibration and verification routines (planned, consistent, auditable)
- Data integrity controls (time synchronisation, retention, access control)
- Event handling (acknowledgement, investigation notes, corrective actions)
- Reporting outputs that stand up to review (clean exports, consistent time-series, and clear incident narratives)
External reference (DWI standards/regulations):
https://www.dwi.gov.uk/drinking-water-standards-and-regulations/
AQUAIOT drinking water monitoring context:
https://aquaiot.co.uk/urban-drinking-water-quality-monitoring-uk/
Connectivity for dispersed and underground assets: LoRaWAN vs NB-IoT
Connectivity is not a box-tick; it affects battery life, uptime, and scaling speed. In practice, many programmes use a hybrid approach: LoRaWAN where you can control coverage (dense estates, gateway strategy) and NB-IoT where assets are geographically dispersed and you want rapid rollout without deploying gateways.
AQUAIOT guide:
https://aquaiot.co.uk/lorawan-vs-nb-iot-water-uk-smart-water-connectivity/
The key is to choose connectivity based on site constraints, expected payload frequency, and the operational impact of missed messages — not just headline coverage.
Best 7-step delivery plan: pilot to scale without chaos
Step 1: define outcomes before you buy kit
Pick two or three outcomes you can prove: reduced incident duration, faster response, fewer emergency call-outs, clearer prioritisation, or stronger audit readiness.
Step 2: instrument Tier-1 sites first
Start where the risk, scrutiny, or impact is highest. Early wins build internal confidence and unblock scaling.
Step 3: deploy event monitoring with operational context
Event truth alone is not enough; include enough context to interpret and act on events reliably.
Step 4: add upstream/downstream monitoring where it creates clean comparisons
For Section 82 water quality compliance, focus on placements that reduce confounding signals and build defensible evidence.
Step 5: build real-time alerts around duty reality
Align escalation to duty cover, contractor SLAs, and acknowledgement workflows. An unowned alert is just noise.
Step 6: prove data quality continuously
Track comms uptime, sensor health, and maintenance history. Trust is everything in operational monitoring.
Step 7: report outcomes, not dashboards
Show what changed: response time, incident frequency, time-to-investigate, and intervention effectiveness.
RFP / framework checklist
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Event Duration Monitoring (EDM) sensors requirements (event evidence, uptime targets, asset identification, data gaps rules)
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Section 82 water quality compliance approach (upstream/downstream strategy, parameters, maintenance model)
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Real-time CSO overflow alerts (threshold logic, escalation, acknowledgement, audit trail)
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Data governance (access control, retention, time sync, exports)
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Connectivity (LoRaWAN / NB-IoT / hybrid) and underground performance assumptions
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Maintenance and calibration plan (including anti-fouling strategy where required)
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Integration (API/webhooks/SCADA alignment if needed)
Conclusion: evidence that prevents pollution, not just records it
Event monitoring provides the operational truth of what occurred at the asset. Section 82 monitoring helps build the receiving-water evidence that supports defensible prioritisation and better outcomes. Add real-time alerting and a governance-ready data trail, and you move from passive reporting to prevention and control.
If you want a scoped pilot (event monitoring + receiving-water monitoring + alerts + reporting), speak to AQUAIOT:
https://aquaiot.co.uk/contact/