As it says on the main page, I had a dual career in Waterworks and Sewer: I started as their IT manager, then got back into the Engineering job family as their GIS developer, and designed the GIS mapping system they use for all the maps of water, sanitary, and storm sewers.
With that, and a major corrosion-protection program, I figure we saved the City of Calgary about a hundred million dollars on pipes they didn't have to replace.
My main role was to listen carefully to technicians and follow their advice. More engineers should. The corrosion technicians who championed, designed, managed, and carried out the program (I signed cheques and made presentations to management on how we should listen to them), were:
Bill Ng, Brad James, Richard Roe, and Murray Hoines. With Gregg Garbut and Rod Engel carring on their work after they retired. Fellow professional engineers: listen to your technicians, that's all I've got to say.
Here are the highlights:
It took about 20 years, but I finally developed a statistical model that would predict the likely number of main-breaks for the next year of a water pipe; a model that could be applied across an entire pipe database to give a risk, in dollars-per-metre, for each pipe, constantly. The database was then updated every night for risk levels, changed after every main break. It could then always print out a prioritized list for replacements.
Basically, I automated my own job of picking the yearly replacements by hand.
My successor was able to expand her duties considerably, get out in the field more with the new inspection technologies. We co-wrote the paper on my model, delivered at the Western Canada Water and Wastewater Conference in Calgary, spring 2016, right after I retired.
PowerPoint file for "Calgary Water Main Break Prediction Model" All the speaking notes to go with each slide are included, so you can follow the whole presentation.
(added 2025): The model, incidentally, came from filling in a probability table with the results of over 300,000 "cases" of mains that broke, or not, over 50 years - a "machine learning from large data" model. While we didn't call it such, that approach is now called "AI".
We started the program in 1998 and it still goes on, may now mostly be re-retrofitting anodes that wore out over 20 years, to keep the main going another 20. I estimated around 2015 that it had already averted a thousand main breaks, saved over 20 million repair dollars and a hundred million replacement dollars; by now, you can add a good third onto those numbers.
I never did do a public presentation about it - they were all internal, for my management. Here's a few slides I can show.
The last several years of that career, my job was expanded to sanitary and storm sewers, when the two departments merged. Having developed a general approach to the "risk of a main" problem for water pipes, I was able to find an equivalent for sewer pipes: a model where the various things in its history (video inspections, past repairs) could predict the risk of future dig-repair needs, future flushing needs, and prioritize by risk. That model needed a lot more consideration of the "consequences" of failure, much higher if sewage spills into the environment than the street. A new engineer-in-training worked on that, under me, and we did a paper at the same conference about the equivalent sanitary-sewer risk model and rehabilitation priorities.
PowerPoint file for "Calgary Sanitary Sewer Risk Model", again including the whole speech.
I was pretty proud, though. I solved - for Calgary, at least - the Holy Grail of Asset Management: entirely automatic risk prioritization. Then I did it again, for a quite different asset class. Most utilities still make these decision entirely by "gut-feel", or by rules-of-thumb. I'd found our old rules-of-thumb to be very wrong, in the course of developing a scientifically-defensible replacement. The fact that I was able to do it again, in such a short time, shows that the methodologies I developed remain valid, despite the type of infrastructure; they are general principles.
Utilities around the globe, but especially where there is a lot of old infrastructure, are wasting billions per year on replacement by poor guesswork. The "infrastructure crisis" is bad, but not actually quite as bad as many engineers portray it; with good data and good decisions, with new inspection and rehabilitation technologies, we can get a lot more value out of old infrastructure than we think.
Others carry on with these models at The City of Calgary Water Resources, but I hope they find application across the industry.
The infrastructure-evaluation methodologies I developed were for whole asset types (all 50,000 water pipes, say) where you have limited information about them. Pipeline inspection technologies bring your information to a whole other level, allowing for near-certainty about the pipes inspected. It's where you go next when the statistical models indicate a concern.
Presentation to Ontario Waterworks Assocation, 2016
Powerpoint of my Presentation to the National Association of Trenchless Technologies 2019, Denver, CO
Powerpoint of my Presentation to the American Waterworks Conference Workshop on Water Pipe Management2019, Chicago, IL
(There's some overlapping material between the two).
Geographic Information Systems
Some Examples of work from my career - GIS maps of Calgary Water systems
Waterworks Infrastructure Management
Anode Retrofit Program
The thing I helped along that did more good than any of the other things I brag about on this page (Main Break Prediction Model, Pipeline Inspections) was the retrofit of magnesium anodes on iron mains as a corrosion-protection system.
Sewer Infrastructure Management
Infrastructure Databases and Automation of Engineering Decisions
So it was quite the photo-finish to a career; the Sanitary Model showed a high correlation coefficient indicating statistical value, only weeks before I retired, was presented months after I did.
Pipeline Inspection Technologies
Speaking of new inspection technologies, I gave three presentations in retirement that explore the very state-of-the-art in pipe inspection, an industry where my native Alberta is an unquestioned world leader. I was very lucky to have worked with both Pure Technologies, and especially with PICA, both proud examples of Alberta's high-tech consulting to the world.
The Last AWWARF Paper I Worked On
I contributed to a number of papers by the American Waterworks Research Foundation; for this one, I wrote enough that I got credit at the top, so I'll post it here. The experience certainly soured me on doing any more for AWWARF, or at least with consulting company HDR. (They contrived so that my work on the paper was done at little more than minimum-wage.) Basically a volunteered professional courtesy to the very few engineers that would like to read:
"Leveraging Data from Non-Destructive Examinations to Help Select Ferrous Water Mains for Renewal" (2016)
Good Summary of My Whole Job
This PowerPoint Presentation (speaking notes are included) to the Canadian Network of Asset Managers in 2012 was a 20-minute summary of 10 years of "Asset Management" work, (some of which went back 20 years, really) for both the Water and Sewer utilities. For those with only 20 minutes or less, this would be the quickie version of my career story.