Manhole Inspection Prioritization Using Risk-Based Models

21 November 2025

Manhole inspections compete with a long line of public works priorities, from resurfacing roads to replacing failing culverts. Everyone wants a clean sewer system that quietly does its job; few notice it until sewage backs up in a basement or a sinkhole opens in a street. That tension is exactly why risk-based prioritization matters. When budgets are tight, the sequencing of inspections often matters more than the inspection method itself.

Cities that rely on first-come scheduling or a simple age-based rotation leave value on the table. They spend too much time inspecting assets that are unlikely to fail and not enough time where a break could cause real damage. A risk-based model reorders the queue using consequence and likelihood, then trims the fat with data from the field, especially video pipeline inspection and service call histories. When done well, the approach is not academic. It is a practical way to cut overflow incidents, reduce emergency callouts, and stretch limited inspection crews farther.
What “risk-based” really means for manholes
In wastewater and stormwater systems, risk is the product of how likely an asset is to fail and how bad that failure would be. The nuance lives in how you define those two halves for a single, often overlooked structure: the manhole.

A manhole rarely fails in isolation. It functions as a node that ties together pipe segments, service laterals, ventilation, and access for hydro-jetting and repairs. When a manhole experiences severe deterioration, it can collapse structurally, allow groundwater infiltration that overloads treatment plants, or act as the weak link that triggers surcharge and overflows during storms. All of that suggests that manhole risk must account for not just the manhole itself, but its context in the network.

In practice, likelihood scoring relies on a blend of observable condition, environment, and operational indicators. Consequence scoring relies on location, connected customers, critical facilities, and exposure routes like storm inlets or waterways. Put together, they give you a defensible ranking that your operations teams, finance staff, and council members can understand.
Anatomy of a practical risk model
Ignore the temptation to build a black box. An effective risk model for manhole inspection prioritization should be simple enough to audit and flexible enough to adapt with new data.

Start with a baseline formula that multiplies a normalized likelihood score by a normalized consequence score. To keep it tractable, pick three to five inputs for each side. You can expand from there as your data improves.

Likelihood inputs that typically pull weight:
Condition evidence from the last inspection cycle or from nearby CCTV runs. Even if you have not inspected the manhole itself, video pipeline inspection upstream and downstream reveals defects like root intrusions, joint offsets, or sags that often correlate with manhole problems such as infiltration or bench failure. Environmental exposure. Groundwater elevation relative to the manhole invert, soil type, and corrosivity. In sandy soils, settlements and cone failures are more common. In high groundwater areas, infiltration and buoyancy become bigger risks. Operational stress. Known surcharge events, grease hotspots, and frequent blockages. If a district requires hydro-jetting more than twice per year to maintain flow, that is a signal. Age and material. Brick and unlined block structures age differently than cast-in-place concrete or polymer liners. In some cities, bricks hold up for a century; in others with aggressive hydrogen sulfide, they decay fast. Let local experience drive these weights. Construction attributes. Drop structures, shallow covers under heavy traffic, or lids with poor seating increase likelihood of damage or intrusion.
Consequence inputs that consistently matter:
Public health and environmental receptors. Proximity to schools, hospitals, nursing homes, surface waters, and beaches. A single overflow near a trout stream carries more consequence than one in an alley with contained flow. Customers affected. Count the downstream connections and any critical users like laboratories or food processors with high production sensitivity. System criticality. If a manhole sits on a trunk main with no redundancy, the consequence of failure is high. Local collection lines with parallel routes can tolerate a temporary outage better. Surface context. High-traffic intersections, rail crossings, and arterial roads escalate consequence because access for repairs is harder and disruptions carry higher social costs. Regulatory pressure. Consent decrees or known overflow basins should receive heightened consequence scoring to reduce violations.
Weight each input transparently. If you are just getting started, use equal weights and adjust after review. Most agencies move to weights that emphasize consequence over likelihood by a modest margin, something like 60-40, because severe impacts are politically and financially costly.
Data you need, and the compromises you will make
The best model is the one you can actually feed. Many utilities face gaps: scattered inspection records, inconsistent GIS attributes, or condition grades recorded in PDFs instead of databases. Accept imperfection early, then design a data diet the model can digest.

GIS should hold a unique ID for each manhole, coordinates, rim and invert elevations if available, material, diameter, and a few key flags such as drop or lined. Service calls, blockages, and overflow logs should be geocoded and linked to the nearest manhole ID. For likelihood, you also need condition observations. If your crews run video pipeline inspection on adjacent mains, use codes for infiltration, corrosion, and root severity as proxies.

Consequence needs demographic overlays, critical facility locations, floodplains, streams, and traffic categories. If you lack traffic data, roadway functional class works surprisingly well as a surrogate. In one mid-size city I worked with, simply tagging “arterial,” “collector,” or “local” along with a school buffer captured most of the consequence variation that mattered for planning.

A word on precision: do not spend six months perfecting a groundwater map if you have glaring holes in blockage histories. Focus first on what explains most of the variance, then add refinements.
Turning risk into a field-ready inspection plan
Once you have a risk score for every manhole, you still need a plan that crews can execute. Too many models end at a ranked spreadsheet. Operations staff need blocks of work by area, a mix of quick wins and high-risk assets, and accommodations for traffic control and permit constraints.

Cluster the top-ranked manholes geographically so one truck can inspect 40 to 60 in a day, depending on spacing and access. Choose clusters that share traffic conditions and work windows, like downtown night work or school zones outside dismissal hours. It is common to slice the top 10 percent by risk, then form clusters that keep gear, safety setups, and traffic control consistent across a shift.

Hydraulically, consider where surcharge is likely. When you find a high-likelihood manhole in a basin with repeated wet-weather complaints, schedule it alongside a short CCTV run of the connected main. This paired approach avoids orphan findings. The manhole and its upstream and downstream segments tell one story.
How video pipeline inspection changes the picture
Video pipeline inspection is the x-ray that turns a rough model into a living plan. The trick is to treat the footage as structured data, not just a memory card full of images. Adopt a defect coding standard, whether NASSCO PACP/MACP or an internal schema that can map to it. Then use summary scores to adjust likelihood in near real time.

A practical field loop looks like this. Crews inspect a cluster of manholes, and within a week an analyst grades the footage and codes defects. Where adjacent mains show severe root intrusion or active infiltration at joints, bump the likelihood score for the next inspection group that shares that soil type or groundwater condition. Conversely, if a corridor of old brick manholes looks remarkably sound, redistribute crew time to the next hotspot. You will end up with a rolling six-week plan that changes slightly every Monday. Operations staff prefer this tempo over an annual plan that is obsolete by spring.

One lesson that repeats: do not overreact to a single dramatic video. Anchor changes to patterns across several assets in the same context. If four manholes along a clay tile main show moderate infiltration, it is a trend. If one looks pristine and the rest are poor, that outlier may reflect a localized repair, not a basin-wide reprieve.
The role of hydro-jetting and cleaning data
Hydro-jetting records are an underused signal. If crews return to the same locations more than twice a year to clear roots or grease, your model should reflect elevated likelihood. The pattern often traces back to a small number of severe contributors: a restaurant block without a grease trap enforcement program, a stand of trees with aggressive root systems, or a sagged section that collects debris.

Fold jetting frequency and debris type into your likelihood score as a low-weight but meaningful factor. Track footage of each jetting run like you track CCTV: date, segment, manhole IDs, debris type, volume estimate. The difference between a light pass and a heavy extraction tells you something about how quickly a blockage returns. Over time, your model can reduce inspection intervals in those pockets until a root treatment, point repair, or lining changes the conditions.
How to calibrate: ground truth beats elegance
Every risk model carries biases, especially at the start. Calibration is how you quiet them. Pick a pilot basin that includes a variety of materials and land uses. Run your first pass risk scores, then inspect a stratified sample: some high-risk, some mid-risk, a few low-risk. Compare predicted likelihood to observed condition.

Adjust weights where your predictions miss repeatedly. If you overpredict deterioration in cast-in-place concrete under low H2S loads, reduce the material weight. If your model misses liners that are failing at the seams in flat terrain, add a factor for surge history or adjust how you interpret bench condition. Recalibrate twice a year for the first two years, then annually.

Document why you change weights. That transparency builds trust with crews, who will notice when the list does or does not reflect their experience. I have seen models fail politically, not technically, because they ignored what field staff knew to be true about a neighborhood.
Budget alignment and inspection intervals
Risk informs not just which manholes to inspect first, but how often to revisit them. Rather than a fixed three-year cycle for all assets, use variable intervals that reflect risk tier. High-risk manholes might return to the list every 12 to 18 months. Moderates might see a 3 to 5 year rotation. Low-risk assets can stretch beyond 7 years, especially if the surrounding mains show stable conditions.

Tie intervals to budget chapters. If your typical inspection crew costs 1,200 to 1,500 dollars per day fully loaded, and you can inspect 50 manholes per day in mixed urban conditions, then a 300,000 dollar annual budget buys roughly 10,000 inspections. With 25,000 to 35,000 manholes in a mid-size city, that means a complete pass every 3 to 4 years only if you keep the low-risk bucket on a longer cadence. A risk-based approach makes that math work without sacrificing reliability.
Integration with rehab planning
Inspection prioritization should not be divorced from rehabilitation planning. A common failure mode is to discover defects faster than you can fix them. Then the backlog grows and the model loses credibility. The better approach is to align inspection clusters with likely rehab batches.

If a risk cluster points to a corrosion corridor, follow with MACP level detail during inspection so engineers can specify liners or coatings without repeat visits. Where video pipeline inspection indicates mainline defects are the primary issue, plan multi-asset projects that address both the manholes and the critical pipe segments. You gain economies of scale in traffic control, mobilization, and permitting.

Use consequence to stage order of construction. The highest consequence corridors get first crack at the rehab budget, even if their likelihood is only moderate. Your regulators will appreciate the reduction in overflow exposure, and your customers will notice fewer disruptive failures.
Edge cases and judgment calls
Not every case fits the model. A few patterns deserve careful human override.

Sinkhole precursors. Depressions around frames, rocking lids, or sudden settlement near utility crossings indicate voids. Queue an immediate inspection, regardless of the risk score.

Vandalism and unauthorized access. In some neighborhoods, open or broken lids appear repeatedly. The physical risk to the public outweighs the model’s predicted consequence. Assign priority by safety, not hydraulics.

Newly lined corridors. Fresh lining can make a model complacent. Keep a closer eye for the first 12 to 24 months to ensure no reinstatement leaks or annular inflow appear. After that window, you can relax intervals.

Shared structures with storm systems. Combination manholes or cross-connections change failure consequences. The path from sanitary overflow to a storm outfall reduces travel time and warning. Weight consequence higher.

Construction seasons. In cold regions, winter limits paving cuts and can slow traffic control approvals. Rotate the plan to emphasize off-street or low-traffic areas in winter and save downtown arterials for shoulder seasons. The model can flag risk, but operations reality decides the order.
Building the field package: what crews need on day one
A good plan still fails without a usable field package. Give crews maps with route order, access notes, and safety flags. Include recent service calls and any known hazards like deep drops or confined entry idiosyncrasies. For each cluster, specify the target count for the day, the order of priority within the cluster, and the threshold for calling an engineer in the field.

Short feedback loops matter. Crews should record conditions in a structured form, preferably on a tablet linked to your asset system. They should also have a way to mark anomalies that the form does not capture, with photos and short notes. That freeform field judgment often points to risks you did not model, like recurring lid theft or irrigation inflow from a nearby property.
Measuring success beyond a neat dashboard
The principal outcome is fewer failures with the same insight underground solutions https://www.google.com/search?q=InSight+Underground+Solutions+Sewer+Cleaning+%26+Inspection&kgmid=/g/11yb1lwb2g#lpstate=pid:-1,av or smaller inspection volume. Track three indicators quarterly: sanitary sewer overflows per 100 miles, emergency callouts per 1,000 manholes, and percent of manholes inspected that require follow-up work orders. If the first two decline while the third holds steady or rises, you are catching more issues earlier.

Also track schedule adherence and rework. Risk-based models that change weekly can cause churn if you do not manage the pipeline tightly. Aim for a six-week rolling plan with changes limited to 10 to 20 percent each week. Keep a small reserve day every other week to tackle urgent finds without derailing the schedule.

Finally, watch for geographic equity. Concentrating exclusively on high-risk corridors can inadvertently neglect lower-income neighborhoods that do not have obvious critical facilities but still deserve reliable service. Incorporate a soft cap that ensures each district sees a minimum inspection rate over a multi-year horizon.
Case vignette: a six-month turnaround
A suburban utility with about 18,000 manholes struggled with wet-weather overflows along two trunk lines. Crews spent much of their year reacting to blockages and cleaning the same hotspots. They had partial inspection records, mostly paper, and a GIS that was 80 percent complete.

We stood up a basic risk model in three weeks with five likelihood and four consequence inputs. Likelihood leaned on recent video pipeline inspection of the trunk mains, jetting frequency, and material. Consequence used road class, overflow history, and distance to a creek. The team clustered the top 12 percent of manholes into 14 work zones, each about 250 to 300 assets.

In month two, as footage came in, we adjusted weights after noticing a pattern of infiltration in brick manholes near an old stream channel that was buried in the 1950s. A digitized historical map, overlaid with groundwater depth, improved prediction sharply. By month four, emergency callouts had dropped by about 35 percent compared to the same period the previous year, even though rainfall totals were slightly higher. We found 74 manholes with severe bench loss or active infiltration requiring near-term rehab, and we sequenced them into three bundled contracts to avoid repeated traffic setups.

The crew superintendent’s verdict was clear: the work felt organized. That is what a risk-based approach buys you, beyond the statistics.
Where video and analytics can go next, without overcomplicating
There is a temptation to leap to fully automated defect detection right away. Resist the urge until your basic data flows are clean. The biggest wins often come from routine discipline: timely coding of video pipeline inspection, consistent hydro-jetting logs, and a weekly triage meeting where engineers and crew leads adjust the plan.

That said, two analytical additions pay back quickly. First, a simple trend model that flags basins where inspection findings deteriorate faster than expected, prompting shorter intervals. Second, a change-point alert when service calls spike in a district, triggering a rapid inspection mini-blitz before problems cascade.

When you are ready for more, experiment with image-aided consistency checks rather than full automation. For instance, have software highlight frames likely to contain infiltration or corrosion so reviewers can confirm quickly. The goal is speed and consistency, not a replacement for trained eyes.
The quiet discipline that keeps it working
Risk-based manhole inspection is not a one-time project. It is a management habit. Keep the model transparent, the data tidy, and the field feedback loop short. Treat video pipeline inspection and hydro-jetting records as first-class citizens in your asset system, not attachments someone might look at later. Revisit weights when you learn something new, and capture that lesson in the model with a note that future staff can read.

Most important, keep score in human terms. Fewer late-night callouts. Streets that stay open. Basements that do not flood during a summer storm. Those are the outcomes that justify the spreadsheets and the long meetings. And those outcomes arrive faster when you put the highest-risk manholes at the front of the line, for reasons you can explain and defend.

InSight Underground Solutions Sewer Cleaning & Inspection
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Address: 1438 E Gary Rd, Lakeland, FL 33801
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Phone: (863) 864-5790

InSight Underground Solutions Sewer Cleaning & Inspection

<br>

Address: 1438 E Gary Rd, Lakeland, FL 33801

<br>

Phone: +18638645790 tel:+18638645790

<br>

<h2>FAQ About Video Pipeline Inspection Services</h2>
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<h3><strong>Will insurance cover a CCTV sewer inspection?</strong></h3>

In most cases, homeowners insurance does not cover routine CCTV sewer inspections as they are considered preventative maintenance. However, if the inspection is needed to diagnose damage caused by a covered peril like a sudden pipe burst or backup, your insurance may cover it depending on your policy terms and deductible.

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<h3><strong>Why is sewer video inspection cost so expensive?</strong></h3>

Sewer video inspection cost varies based on several factors including the length and depth of your pipeline, accessibility issues, the complexity of your sewer system, the type of CCTV equipment required (standard vs. advanced with lateral launch capabilities), and whether the inspection includes a detailed report with recordings and GPS mapping for future reference.

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<h3><strong>Is it cheaper to hire CCTV pipe inspection contractors or go through my city?</strong></h3>

Private CCTV pipe inspection contractors typically offer more flexible scheduling and competitive pricing compared to municipal services, but costs vary by location and scope of work. To determine which option is most affordable for your situation, you'll need to get quotes from both private contractors and your local utility department if they offer the service.

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<h3><strong>What is CCTV sewer inspection certification and why does it matter?</strong></h3>

CCTV sewer inspection certification ensures that technicians have received proper training in operating specialized camera equipment, interpreting pipeline conditions, identifying defects according to industry standards like NASSCO PACP (Pipeline Assessment and Certification Program), and producing accurate inspection reports that comply with municipal requirements and engineering specifications.

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<h3><strong>How do I find video pipe inspection near me?</strong></h3>

To find video pipe inspection near you, search online for local CCTV pipe inspection contractors, check reviews on platforms like Google and Yelp, ask for referrals from plumbers or property managers, verify their licensing and insurance, and request quotes from multiple providers to compare pricing, equipment quality, and turnaround time for inspection reports.

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<h3><strong>What are typical CCTV sewer inspection jobs and career opportunities?</strong></h3>

CCTV sewer inspection jobs include positions as field technicians operating camera equipment, video analysts reviewing and coding inspection footage, project coordinators managing large-scale municipal pipeline assessment programs, and senior inspectors with certifications who train others. The field offers stable employment with municipalities, utility companies, engineering firms, and specialized Pipeline Video Inspection LLC companies across the country.

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<h3><strong>How long does a pipeline video inspection take?</strong></h3>

A typical residential sewer video inspection takes 1-2 hours depending on the length of your sewer line and complexity of the system, while commercial or municipal pipeline video inspections can take several hours to full days based on the scope of work, number of access points, and whether additional services like cleaning or lateral inspections are included.

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<h3><strong>What problems can a sewer video inspection near me detect?</strong></h3>

A professional sewer video inspection near you can detect various issues including tree root intrusions, pipe cracks and fractures, collapsed sections, grease buildup, corrosion, misaligned joints, bellied or sagging pipes, blockages from foreign objects, and connection defects, providing you with visual evidence and precise location data for targeted repairs.