WIPAC Monthly July 2019

WIPAC MONTHLYThe Monthly Update from Water Industry Process Automation & Control
www.wipac.org.uk Issue 7/2019- July 2019

In this Issue
WIPAC Monthly is a publication of the Water Industry Process Automation & Control Group. It is produced by the group
manager and WIPAC Monthly Editor, Oliver Grievson. This is a free publication for the benefit of the Water Industry and please
feel free to distribute to any who you may feel benefit. However due to the ongoing costs of WIPAC Monthly a donation website
has been set up to allow readers to contribute to the running of WIPAC & WIPAC Monthly, For those wishing to donate then
please visit https://www.patreon.com/Wipac all donations will be used solely for the benefit and development of WIPAC.
All enquires about WIPAC Monthly, including those who want to publish news or articles within these pages, should be directed
to the publications editor, Oliver Grievson at olivergrievson@hotmail.com
From the editor............................................................................................................. 3
Industry news..............................................................................................................
Highlights of the news of the month from the global water industry centred around the successes of a few
of the companies in the global market.
4 - 11
Is it time to revamp the SWAN Layers?..........................................................................
In this month’s feature article, in light of comments this month, we examine whether or not it is time the industry
revamp the SWAN Layers which have been the mainstay of the Smart Water Industry.
12-14
The top 10 real-time water analytics.............................................................................
In this article by Jason Colton and Tom Lendrem the analytics used in water treatment plants are examined looking
at the top ten real-time water analytics
15-16
The basics of aeration control valves.............................................................................
In this technical article which part 1 of a blog by Tom Jenkins of Jentech we examine the basics of aeration control
valves.
17-19
Moving towards Maintenance 4.0.................................................................................
Christopher Steel of engineering firm, Black & Veatch examines the concept of Maintenance 4.0 and Dynamic
Maintenance where a combination of data and deep-institutional knowledge is used to drive maintenance
programmes.
20-21
Workshops, conferences & seminars............................................................................
The highlights of the conferences and workshops in the coming months. 22-23

From the Editor
Arguably, one of the fundamental building blocks of the smart water industry is the SWAN Forum layers diagram
describing the five layers from infrastructure to analytics. This month there has been a bit of a discussion over
whether the layers completely describe a structure for the industry. There have been discussions this month as to whether
on a technical front the industry should include aspects of Machine Learning and Artificial Intelligence or a more business
front things aspects such as business cases and the people elements of the industry. It something that I’ve addressed
in this month’s feature article and I argue the factor that the technical factors are already included and aspects such as
business cases and other aspects of business processes as well as the people aspect are actually a factor of every single
layer of the SWAN Forum layers diagram.
All of this is, of course, are the horizontal, systematic, business-wide aspect of the smart water industry however there are
the vertical application segments too. Non-revenue water is something that is well-established within the water industry
and is set to be all important in the next Asset Management Period (AMP) in the United Kingdom with an average of a
15% improvement in leakage required across the industry. However more vertical segments are coming into sharp focus. The Zero-Pollution Summit that took
place earlier this month saw every single water and sewerage company represented along with every single regulator all talking about how we could deliver
the lofty aim of zero pollution incidents. It was at this summit that we heard from the regulator who had the basic message that nothing is improving in this
area with the number of pollution incidents remaining basically static. The smart water industry has its part to play in improving this figure but people and
processes, the other two dimensions in the technology triangle, do as well. What this does go to show is that apart from the vertical segment associated with
non-revenue water is not the only market for the wider water industry to concentrate on and the wastewater system as a whole is a much wider area which
is open to technological developments.
It is through these vertical segments, where the particular pain points of the industry exist, that we will see the development and application of the smart water
industry (whether it is in the areas of water or wastewater) as the key to the adoption of the concept is within the application and how the technology can
support and address the problems and the investment areas that the industry has at the current time. I’m often asked why the adoption of the technological
solutions is not more rapid and my answer is always surrounds the fact that any technology that is going to adopted must be able to address a specific
application i.e. a vertical segment. This is not to say that the horizontal elements don’t need to be addressed to in a way that supports the people and the
processes whilst having a solid business justification. The most successful technologies that have been adopted so far within the industry have done both
insofar as they have addressed the horizontal elements within a particular vertical segment. This way a complete solution has been provided making the
adoption a relatively simple business case.
What all of this says is that any technological solution, as per the technology triangle, has to address both the business process and people elements too.
Without all three of these elements covered then any solution with surely fail in the medium to long term. All of this accepting the fact that the technological
solution within the concept of the smart water industry (or not as the case maybe) is not a panacea to address all of the pain points within the water industry
but what it can do is assist the technical and operational experts in the industry to resolve the issues that need to be resolved.
Have a good month,
Oliver

Environment Agency warns water companies to clean up their
act
Water company efforts to protect the environment have been described as ‘simply unacceptable’ in an Environment Agency (EA) report published his month with
only one of the major water and sewage companies in England performing at the level expected. According to the report, overall water company performance
has deteriorated which reverses the trend of gradual improvement in the sector since the rating system began in 2011. Serious pollution incidents increased in
2018 causing damage to both rivers and wildlife.
Environment Agency Chair Emma Howard Boyd, who has previously warned water companies they would face a tougher regulatory approach with increasing
inspections, is pledging that the Environment Agency will continue to work with Ofwat to look at financial penalties to drive better environmental performance
given fines are currently only a fraction of turnover.
Writing in the report’s foreword she said:
“Companies should be reflecting on their environmental performance and long-term resilience, if this is poor they should be asking themselves whether
dividends are justifiable.”
The annual report rates each of the nine water and sewerage companies in England as either green, amber or red on a range of measures including serious
pollution, pollution per km of sewer pipes, supply resilience, self-reporting of pollution and complying with permits – and also compares individual company
performance to highlight the best and worst.
Northumbrian Water was the only company achieving the highest 4 star rating, showing that it is possible to bring in good environmental practices and limit the
impact of operations on nature. The Environment Agency report said this improvement is to be applauded which had only been possible with focus from the top
of the organisation and ongoing effort from operational teams.
The report highlighted the best and worst performance including:
• Northumbrian Water had improved to gain the highest rating of 4 stars.
• Severn Trent Water, United Utilities and Wessex Water dropped from 4 stars to 3 stars, with Anglian Water and Thames Water remaining on
3 stars. Companies with 3 stars must improve their performance to reduce their impact on the environment.
• Southern Water, South West Water and Yorkshire Water were only given 2 stars and described as demonstrating an ‘unacceptable level of
performance.’
• Again this year South West Water is poor performing and has consistently demonstrated unacceptable performance and a red rating for
pollution incidents.
• Most water companies look set to fail to meet 2020 pollution targets.
• Southern Water and Thames Water failed to demonstrate they have robust enough plans to maintain secure water supplies.
Executive Director of Operations Dr Toby Willison said:
“Water companies need to clean up their act. People expect water companies to improve the environment, not pollute rivers and ensure secure supplies of
water.
“With only one exception, none of the companies are performing at the level we wish to see, the country expects and the environment needs. We will continue
to challenge CEOs to improve company performance and we will take strong and appropriate enforcement action.
“Companies performing well have a positive ripple effect on the natural environment and communities in their regions. We want all water companies to meet
the expectation of their customers, the needs of environment and learn from the best practice that the leading company is demonstrating.”
The Environment Agency report can be downloaded by clicking here
Page 4
Industry News

SEW and Vodafone pilot NB-IoT leakage solution
South East Water is working with Vodafone on a pilot that the water company believes is likely to revolutionise leakage detection and prevention. The trial, now
underway in Kent, will run for a year and is the first in the UK to include Narrowband Internet of Things (NB-IoT) as part of a smart water network.
Vodafone and South East Water worked with partners to develop and connect specialist
digital water meters, sensors and acoustic loggers on underground mains water pipes
via Vodafone’s NB-IoT network.
Data will be collected and transmitted across the system and advanced analytics will be
used to monitor readings and alert South East Water immediately in the event of a leak.
Acoustic loggers ‘listen’ for escaping water within the network to determine when leaks
have occurred and to pinpoint the precise location.
NB-IoT operates within a very narrow radio band frequency. This means it can provide
wider coverage and deeper penetration than traditional networks – even underground
or within buildings.
It also operates at low power so that batteries within IoT devices in the field, such as
sensors, can last up to 10 years. This combination ensures that NB-IoT solutions are
more sustainable and less expensive to install and run than current alternatives utilising
4G or fixed line networks.
Anne Sheehan, Vodafone Business director, said: “This is a really exciting project. NB-IoT technology has the power to transform the utilities sector. It provides
a more accurate way of identifying and preventing leaks, helping companies like South East Water meet important regulatory and environmental standards.
“It is a perfect example of how technology can be used to create a more sustainable future and manage what is an increasingly precious commodity.”
Dr Simon Earl, South East Water’s operations director, said: “This trial is likely to revolutionise how we detect and prevent water leaks. The solution has the
potential to alert us to the smallest leak – in either our or our customers’ pipes – as soon as it occurs and could even enable us to predict and prevent pipeline
failure before it happens.
“This has the potential to reduce the water we take from the environment, further minimise interruptions to supply and increase the resilience of the service
we provide to our customers.”
EA to use drones to detect illegal water abstractions
Drones will be used for the first time this summer to gather information about illegal abstraction in East Anglia’s fenland areas. The Environment Agency manages
abstraction to balance the needs of the environment with the rights of lawful water users during periods of dry weather.
The EA’s regulatory officers carry out high-visibility patrols every year throughout the irrigation season to ensure landowners and farmers are adhering to the
conditions of their licences and do not cause harm to the environment.
Last year’s heatwave led to a number of licence holders breaching their conditions and this year some illegal abstractions have already been uncovered.
Andrew Chapman, environment planning specialist for the Environment Agency in East Anglia, said: “Following on from the hot and dry summer we experienced
in 2018, our area has not received the winter rainfall we would normally expect and this is placing significant pressure on the water environment.
“We have contacted irrigators who have licences that permit abstraction from the Middle Level to inform them that restrictions are likely to be required during
the irrigation season.
“We will be prioritising our water resources compliance work over the summer period in those catchments that are at risk from this prolonged dry period.
“This will be the first time we have ever used drones for this purpose. The majority of irrigators do operate within their licence conditions. However, last year a
minority of farmers did not play by the rules and severely restricted other people’s ability to irrigate their crops.”
A third party will be employed to operate the drone, which connects to a web portal, so that an Environment Agency staff member can view the images from a
computer and direct the device to fly over certain locations. If irrigators are found to be abstracting illegally, enforcement action will be taken. This can include
written warnings, civil sanctions, referral to the Rural Payments Agency or prosecution.
Five new environment officers have been taken on this year to help manage the water resources issue. Their role includes identifying licence holders at risk of
water restrictions and making them aware of the possible shortages.
They will also carry out inspections in the riskier catchments where more intense abstraction takes place. In the east of the region, the frequency of compliance
checks and patrols is also increasing.
Michael Neale, Land and Water team leader in Essex, said: “We have an intelligence-led approach to all compliance checks. We will always respond to reports
of illegal abstraction. We are going to up our response out of hours to reports wherever they come from. We will have more resources on hand to bolster our
approach.”
Page 5

Invenio Systems acquired by Halma PLC
Halma PLC has announced this month that it has acquired Invenio Systems. Founded in 2015, Invenio Systems is a market leader in customer-side leak detection,
offering innovative, non-intrusive detection solutions for household leaks. Invenio’s technology identifies leaks on customer property and high water-use
properties for metered billing. The ability to detect customer-side leaks is vitally important to water companies globally, as these areas of the network have
been traditionally difficult to survey.
Invenio will join Halma as part of HWM, creating a global leader in leakage reduction. The combination of HWM’s digital data model and connectivity, with
Invenio’s innovative technology and machine learning capability will create a compelling new value proposition for our UK and international customers.
Remote Noise Logger Trial Pinpoints 115 Leaks
A technology trial involving installation of 295 Enigma3m remote correlating noise loggers in a water distribution network in the State of Johor, Malaysia, has
successfully cut net night flow by a third. Yoo Sun Chan, general manager, Primayer Sdn Bhd, and Roger Ironmonger, managing director, Primayer explain how
the work was carried out.
The state of Johor in southern Malaysia is better known for its beaches and rainforest than its water infrastructure, but water supply company Ranhill SAJ, a
subsidiary of Ranhill Holdings Berhad, has set a challenging target to reduce non-revenue water (NRW) to 5% by 2025.
In December 2018 NRW – loss through leaks, bursts and unauthorised connections - was 24% and a number of actions was set in motion. Firstly, smart district
metered areas (DMAs) of the water distribution network were implemented, with five DMAs involved in the first phase.
UK leakage technology specialist Primayer was approached by Ranhill through Mimtech, the company’s authorised distributor for the southern region of
Malaysia, and the Enigma3m advanced remote correlating noise loggers were deployed in a three-month trial throughout August, September and October 2018.
The aim of the first month of the project was to locate leaks from the correlations obtained from the Enigma3m loggers; during the second month leaks were
repaired and further monitoring was carried out in the third month. The trial was carried on Bandar Putra B DMA in the state capital Johor Bahru, with a total
pipeline length of 38.51km and some 5,052 connections under investigation.
The leakage rate was determined by measuring the net night flow (NNF) and subtracting legitimate night flow from the minimum night flow. Prior to installation
of Enigma3m NNF was 30.99l/s and total daily flow rate was 6,200m3/day.
During the implementation of the smart DMA programme, a total of 295 Enigma3m units were installed by the team from Ranhill Water Services. The Enigma3m
loggers were installed at hydrant valves, air release valves and on exposed fittings along the pipeline. The distance between sites for Enigma3m units varied
depending on whether the pipes were metal or polyethylene.
The Enigma3m loggers installed in Johor use GPRS communications to transmit daily noise data from leaks to remotely locate leaks in water distribution networks,
a major step-up from traditional techniques which include the use of metal rods to listen for leaks from above ground. They are deployed in underground
chambers and require no outlay on surface level equipment.
Deployment of multiple loggers means correlation can be performed, locating leak positions more accurately. Leak location results can be viewed on PrimeWeb,
Primayer’s cloud-based data collection platform for water network pressure, flow and leak location monitoring.
PrimeWeb makes collection of real-time data possible, along with visual display of water network hydraulic data, leak alarms and correlated leak positions.
Ranhill SAJ’s on-the-ground leakage crews were able to locate incidents using Google Maps and, together with street-view visualisation of leak positions,
manage incidents efficiently and effectively.
A total of 115 leaks were found and repaired in Bandar Putra B
DMA during the Enigma3m trial. Small leaks at hydrant valves and
communication pipes were also located. After three months of
Enigma3m installation, NNF was reduced by over a third to 20.08 l/s.
This gives a saving of 705m3/day water, with a total cost saving of
approximately £3,050 (US$4,000) per month.
Zainudin Ngadiran, section head of the NRW control department of
Ranhill SAJ Sdn Bhd, said, “A challenging target for leak reduction
has been set by Ranhill SAJ and we are exploring technologies than
can pinpoint leakage to help us reduce levels of non-revenue water
rapidly. The trials with Primayer have shown that it is possible to
deploy sensors that can precisely locate leaks, enabling our teams to
carry out rapid repairs.”
Ranhill SAJ serves a 3.1 million population and manages 22,175km of
pipes over an area of approximately 19,000km2. The company intends to expand implementation of the Smart DMA concept across Johor state and some of the
state’s most critical DMAs will be managed permanently with Enigma3m, depending on the age of infrastructure and site conditions. It is expected that more
Enigma3m loggers will be required for the expanding programme.
Google Maps graphic showing Enigma3m loggers in situ in Bandar Putra B DMA. Eleven loggers are
pinpointed in red, indicating the locations with the highest likelihood of leakage.
Page 6

Hycontrol release Shield Silo Protection System
Two years after introducing the ground-breaking SHIELD silo protection system, silo pressure
safety experts Hycontrol Ltd are proud to announce the launch of the SHIELD Lite SPS, which
protects powder storage silos from the dangers caused by excessive pressure during tanker
deliveries. Utilising purpose-designed, state-of-the-art pressure monitoring and control
equipment, SHIELD Lite meets and exceeds best engineering practice and current guidance from
the Mineral Products Association. The new, compact panel is designed for simple operation
and to be easily understood, giving users a range of new monitoring and diagnostic tools and
indicating when the system is suffering from blocked filtration or is being endangered by poor
delivery driver behaviour.
Powder storage silos are commonplace in many industries but are at risk of over-pressurisation
during tanker deliveries. The root causes of this are invariably either driver error resulting in
uncontrolled air pressure being discharged during the fill procedure, or a failure of the filter
venting unit. Pressures from as little as 1 or 2 psi are enough to rupture a silo or blow its filter unit
off the top. This poses serious risks, which is why a comprehensive, failsafe safety and control
system is vital.
SHIELD Lite incorporates essential high-accuracy pressure safety components into a modular design that can be adjusted to suit site requirements. Maintenance
is simplified and the long-term cost of ownership is significantly lower than any other system on the market. Along with many new features, SHIELD incorporates
Hycontrol’s pioneering Ground Level Testing, in which a single key-turn enacts a full-function test of all the crucial safety components, dramatically reducing the
need for working at height. Importantly the system is also completely failsafe, a vital feature that’s often overlooked.
“Building on the success of the first SHIELD system has allowed us to develop new tools for site personnel to improve safety,” said Hycontrol Managing Director,
Nigel Allen. “We have insisted for many years that simplicity is the key to safety, and now with developments like ratio alarms, filter blockage warnings and tanker
driver delivery behaviour diagnostics, we can effectively remove the risk of human error completely. Hycontrol has led the silo protection field for more than a
decade through both innovation and product performance. The purpose of developing SHIELD Lite is to make sure that every single pressurised powder delivery
into every single silo is completely safe. We anticipate that customers in the ready-mix and concrete sectors will be impressed by both what this new system can
do and the price we are able to offer it at.”
He adds: “We are determined that safety for staff, contractors and drivers should be the number one priority across all industries. With SHIELD Lite, Hycontrol is
showing that true, failsafe silo safety is not only achievable, but with the right equipment it’s easy, too. We understand that human errors in maintenance and
testing are inevitable. Our philosophy is to accept this, and to provide a system that monitors and safely alerts you when these errors occur. As we say – safe
silos are tested every time.”
Cross-sector learning underpins British Water data conference
Valuable insights into how the water sector can manage data more effectively will be given at an upcoming British Water event this autumn.
Data: Now & Beyond will see speakers from key stakeholders, including water companies and the supply chain, share information and practical advice on the
best way to handle data and analytics – including what tools and services are available.
Organisations from other industries – including Ofgem, Network Rail and Electricity North West – will also share their experiences and give guidance on the fast-
changing landscape of data handling.
This will be British Water’s third data conference, following successful events in 2017 and 2018.
Dr Mar Batista, technical manager, British Watersaid, “Waterand wastewatercompanies collect, process and report on huge volumes of data from their networks,
treatment works, customers and the environment. This data then needs to be turned into valuable information to inform operations, asset management, and
business plans.
“This event is an opportunity to collaborate and, with our industry peers, learn the best ways of working with data, how to get the most from it and how it can
help companies drive efficiencies and improve service.
“We’re delighted that guest speakers from other sectors will be joining us to share their learnings with the water industry. Following the release of Ofwat’s draft
determinations and the challenges set in terms of cost and performance commitments, it’s the right time to look at the innovative use of data and analytics that
will help achieve the high expectations from regulators and consumers.”
The event will also include:
• High-level discussions at a strategic level between water companies, the regulators and supply chain
• Talks on innovation and new technology
• Workshops to encourage problem-solving and diverse thinking
Data: Now & Beyond will take place on Wednesday 9th October 2019 at Cloth Hall Court, Quebec Street, Leeds. Those interested in attending this year’s
conference should register at https://www.britishwater.co.uk/events/data-conference-2019-455.aspx
Page 7

Modern Metering Adoption At Smaller Public Water Systems
As with most things in life, there are those water utilities that have and those that don’t. According to the EPA, less than 3% of the 150,110 operational public
water systems (PWS) in the U.S. serve more than 10,000 people. And those 4,500 systems serve 79% of the population. Not that being big means living trouble
free. Many of these water authorities serve cities plagued by under investment over decades in their water systems. And yet with large rate-bases comes the
means to spread the investment in modern technology across many households and water consumers.
Historically, it’s been a lot harder to invest in new technology for the other 105,110 PWSs who average just 475 consumers per system. And yet advances in
metering technology is making it more efficient than ever before for small PWSs to embrace advanced metering infrastructure (AMI).
According to the Water Research Foundation (WRF), a scientific organization dedicated to the advancement of the water industry, “As advanced metering
technologies become more feature-rich, reliable, and economical, they present greater opportunities and compelling reasons for utility managers to upgrade
their meter reading systems.”
Case Study: Auburndale Public Utilities Department
AMI and smart metering are becoming more popular because of their ability to save costs, improve ratepayer experiences, and more. Smart meters are capable
of collecting water consumption data, rate of flow, indicate reserve flows, and produce alarms automatically when readings warrant it. And with small systems
often supported by a skeleton crew of multi-tasking managers, modern metering technology can provide benefits such as extended low flow accuracy and longer
service life by reducing mechanical bearing friction to lessen the maintenance load.
One smaller public water system that has benefited from AMI is the Auburndale Public Utilities Department. Located in Auburndale, Florida, the utility serves
approximately 11,700 residential and 1,100 water customers.
In 2016, the Public Utilities Department saw a need to upgrade aging infrastructure across its water system. The city’s water meters and endpoints had provided
many years of reliable service, and it was an opportune time to investigate how more advanced technology could benefit the utility and its customers.
To explore new technology options, Auburndale Public Utilities Department leaders spoke with numerous metering manufacturers over the course of several
months. They ultimately chose a managed solution from Badger Meter, combining the BEACON® Advanced Metering Analytics (AMA) software suite with
proven ORION® Cellular communication to deliver a simple, yet powerful, end-to-end solution. In addition, residential Recordall Model 25 Disc Series meters
and E-Series Ultrasonic meters in 1.5- and 2-inch sizes were installed.
The BEACON® AMA managed solution, enabled by ORION Cellular endpoints, has greatly increased efficiencies for Auburndale. Because cloud-based software
suite uses existing cellular networks, it does not require infrastructure or continued maintenance. Now, the Public Utilities Department receives daily, 15-minute
interval water usage data, rather than monthly. This helps the team detect and address leaks faster than ever before and devote more time to other utility and
customer service projects.
But it isn’t just utilities that are benefiting from the advent of smart metering. By providing more data at faster rates and in easy to compute ways, smart meters
and AMI also benefit customers by providing more transparency around costs and consumption. And this becomes critically important in smaller systems where
each consumer shoulders more of the burden for using water efficiently.
With the new water metering system in place, Auburndale Public Utilities Department customers now have more hands-on access to their water usage. The
BEACON AMA solution includes the EyeOnWater® app, which allows water customers to see their water usage in real-time and set alarms when it has reached
a certain level. As a result, the utility has seen a reduction in the time spent managing customer questions.
As WRF notes, “Utility managers who could not justify such systems in the past should periodically reevaluate their feasibility and benefit to water system
operations and customer service.” Piloting a handful of smart meters or simply exploring the specific advantages AMI can bring to your operations with a
technology provider may be the first small step toward great savings, both in time and dollars.
Page 8

Buried less than 10 feet deep and snaking around the world lie more than 1 million miles of stressed, critically-important water pipes that are not getting any
younger. Many have already reached their demise – and will – in emergency settings, within 25 years.
Faced with this challenge, water utilities are turning to new, smarter technology. These include flushable robots to orbiting satellites to help find leaks, monitor
usage, and in some cases, simply find the pipes.
“Nobody knows what’s going on underground,” says Shai Albaranes, VP of Innovation with Mexichem, a world leader in water pipe infrastructure. “When
Mexichem wanted to replace up to four miles of an aging water pipe in Colombia, the customer spent $1 million at the beginning of the project just to
understand where the pipe was.”
Albaranes adds the problem will become even more acute as an ever-increasing number of people move into urban environments. “Ten thousand people are
moving into cities every hour. Urban water networks are not developing at the same speed as urbanization.”
In fact, most city utilities have pipes that are 50 to 70 years old, or 150 in older cities such as New York City.
Singapore is a relatively new city with 5 million people. Yet due to its lack of natural water resources, it has long faced challenges in providing enough water to
its populace. The vast majority of water pipe leaks in Singapore are due not only to aging pipes but issues such as corrosion arising from the high-water table
and high salinity in the soil. Often times, pipes are laid under roads where traffic loads put pressure on them.
The strain on available resources, service interruptions, soaring costs and pressure to raise water rates are unprecedented and are all expected to worsen in the
near future, urban planners say. Billions of dollars in infrastructure repair are potentially at stake. To face the future, new entrants to battle these problems are
tackling it with technology. Watchtower Robotics, for one, based in Boston, has built a “soft robot” that can navigate through what can often be very complex
pipe networks.
The robot is pumped into a fire hydrant, follows the pipe’s operational water flow, then comes out through another fire hydrant. Along the way, sensors inside
the robot act like hands as they ‘feel’ the sides of the pipe for leaks – much in the same way your own hand would feel over a vacuum nozzle. The sensors feel
for the suction created by water escaping the pipe. CEO Tyler Mantel asserts it can pinpoint tiny leaks with reliable location accuracy within four feet.
Inspired by the co-founder’s master thesis in exploring underground water on Mars, startup Utilis
uses the same kind of satellite technology to look for underground water here on earth. Based in
San Diego and Tel Aviv, Utilis uses Synthetic Aperture Radar (or SAR), a type of satellite technology
that uses the L-band wavelength, to penetrate up to 10 feet underground. The bounced back signal
can pick up signs of drinking water as well as leaking pipes, all within a two-block radius. Marketing
Director Karen Dubey says an underground leak can – and often does - go undetected for as long
as 18 months.
Another company, Fracta, based in Redwood City, Calif., offers a Software as a Service (SaaS)
application to assess the condition of water pipes in distribution mains. Fracta uses AI to analyze
data from soil, climate, temperature, slope and the proximity of pipes to buildings and railroads
that could potentially impact a pipe. The aggregated data generated by AI-powered algorithms not
only show which buried water mains are most likely to break but create a digital map of the entire
water network many utilities now lack.
In the U.S. alone, water utilities are experiencing some 240,000 water pipe breaks every year, or
approximately 4,600 each week.
Fracta Chief Revenue Officer Doug Hatler says, “When you think of the hundreds of thousands of pipe segments, how does any human decide which segment
needs to be replaced? The number of factors that contribute to problems are bigger than what engineers alone can handle.”
Phyn is a startup outside of Los Angeles that sends usage data to home owners via a smartphone app. The real-time data show how much water, in aggregate,
is used in homes, whether it be by toilets, sinks or for gardening. Phyn Plus’ sensors are installed by plumbers on the main water supply line and measure tiny
changes in water pressure. This allows Phyn’s machine learning algorithms to understand subtle differences between a running bath and a burst pipe. If usage
is abnormal, an alert is sent to the phone.
“When we talk to plumbers who have been industry for decades, their eyes just go wide,” says Phyn Head of Marketing Jason Rosenthal, “They say plumbing
principles haven’t changed since Roman times, and they’re really excited about the possibilities in disrupting an industry like this.”
Gert-Jan Massdam, Global VP of Market Strategy and Innovation at Mexichem’s water solutions business Wavin, takes a broad view on the situation.
“Watercannolongerbetakenforgranted,”hesays,“Astructuralprobleminbothdevelopedandunderdevelopedeconomiesisthattheagingpublicinfrastructure
in many cities is underinvested and not equipped to deal with water scarcity and the exponentially growing impact of climate change.”
For example, in northern parts of the U.S., heavy freeze and thaw can have a significant effect on water pipes. In the Midwest this past year, massive flooding
occurred with alarming regularity. Aging water systems are not improving with time. The role technology plays may prove critical in helping to solve this global
issue.
Used with the permission of http://thenetwork.cisco.com/
Smart technology now flowing to a tap near you
Page 9
Replacing a water main

Aguas Magallanes Selects TaKaDu’s Central Event Management
(CEM) Solution To Improve Operational Efficiency
Aguas Magallanes, the Southern Patagonia based water company, has chosen TaKaDu as their Central Event Management software provider, being the fourth
customer for TaKaDu in Chile.
Owned by Aguas Nuevas Group, Aguas Magallanes brings the highest international quality standards to the services it provides. Aguas Magallanes reaches the
Austral cities of, Punta Arenas, Puerto Natales and Porvenir, serving over 50.000 clients.
TaKaDu is the leading CEM solution for water utilities, enabling a single dashboard for all network events and incidents. Based on big data analytics and machine
learning, TaKaDu’s cloud-based service detect, analyze and manage network events and incidents such as leaks, bursts, faulty assets, telemetry and data issues,
operational failures, and more. TaKaDu seamlessly integrates with other enterprise IT systems (GIS, asset management, work order management, CRM, etc.) and
detection technologies (e.g. acoustic sensors), delivering a central hub for quicker response times and the fast resolution of events.
Ziv Zaretsky, TaKaDu’s EVP Sales & BD, said “We are proud to land Aguas Magallanes as TaKaDu’s fourth customer in Chile together with our trusted partner Blass.
This is further evidence that the water sector in Chile is very progressive and understands and promotes efficiency and data solutions. We are looking forward
to helping Aguas Magallanes achieve the full potential from the system”.
Andres Calderon Testa, Blass’s Co-Founder, confirmed that water utilities in Chile are taking an active role in Smart Water Networks implementation, aiming to
improve their operations, reduce water losses and deliver high-quality customer service. “We are strongly committed to support our clients on this journey,
bringing closer the Hi-Tech water industry to our country. Currently, fourth of the most relevant water companies in Chile have trusted in TaKaDu, embracing its
solution. This reflects a new way to face water management, which keep us very optimistic about the future of this industry.”
Water Research Foundation releases an RFP for the definition of
a smart utility
The Water Research Foundation, amongst other projects, have released a Request for Proposals for the definition and framework for a smart water utility.
Project funding of up to $75,000 is available for those wishing to take on the project whose three-fold objectives are:
• Based on successful application of Intelligent Water Systems (IWS ) approaches, define concepts and components of an effective data-
driven, digital utility/smart water system, including culture, management and skill sets.
• Leverage ongoing advancements in sensor, data management/analytics, and digital communication technologies.
• Facilitate the use of IWS/data-driven digital utility approaches for optimal management and operation of complex water systems.
In outlining the project background and rationale the WRF recognise the data “revolution” is here. It is well documented that the water sector has more data
being generated and stored than is used. In addition, new data sets will be from new kinds of sensing technologies that can perform edge processing (processing
data in the proximity where they are generated) using battery power and wireless communications. The traditional methods that utilities use for processing data
will be a challenge as new technologies are implemented. Determining how to make the best use of these data can provide insights leading to improvements
across the utility.
Intelligent Water Systems (IWS), also called Smart Water Networks, is a popular topic and utilities face many issues in a rush to become data-driven. Big Data,
the Internet of Things (IoT), machine learning, artificial intelligence (AI), etc. are associated with an IWS. There is a clear need for a coherent model (framework)
or set of management practices and principles to guide a utility in becoming a Smart Utility.
What are the characteristics, the fundamental elements of a smart utility, the basic building blocks, technologies, skill sets, culture and workforce, and how do
they fit into an IWS? An IWS is essential to addressing many issues, such as watershed protection, facility operations, infrastructure sustainability, customer
service, and workforce management. In other words, what is the value to a utility and its customers, as described in a business case, of becoming a Smart Water
Utility?
Recent WRF research underscores the efforts of utilities and their journey toward becoming a smart utility. Essential to becoming a smart utility is a clear
understanding of the various terms, elements, practices, people, technologies and value for the utility and customers. This means that definitions, methods,
asset classes, and individual research areas need a common approach to determining digital projects that begin with the knowledge of the subject.
Research Approach
A research approach that is logical, step-wise, and easily understandable with clearly defined benefits is necessary to help the water sector with IWS efforts.
The research approach should:
• Define a common IWS framework.
• Develop a framework for the fundamental elements necessary for an IWS to assist utilities to become a Smart Utility at their own pace and ability. Include
business case, planning and change management guidance along with how and where to begin because IWS is a journey, not an “all or nothing” effort.
• Discuss utility culture and the digital utility – project management, company organization change, employee talent characteristics.
• Develop Best Appropriate Practices relevant to each part of the framework.
For more information the details of this call for proposals can be downloaded at - http://www.waterrf.org/funding/rfps/RFPs/RFP_5039.pdf
Page 10

Do Your Plant Instruments Play Nice With Others? The Benefits
Of Integrated Technologies
The majority of monitoring devices found throughout a water treatment plant and distribution system — such as sensors for level, flow, and pH — are commonly
analog 4-20mAdc. In other words, there is one output signal from the transmitter, so adjustments need to be made manually at its location. At the same time,
putting the information produced by those devices into context and using it to improve performance through traditional data process management is labour-
intensive.
By comparison, digital signals provide two-way communication, so they can be programmed directly from the control room or with a laptop or handheld
communicator. However, the bigger benefit is that they can be part of a system offering assured interoperability to provide a seamless flow of information. This
type of integration between key components of the water treatment and distribution process improves overall decision-making and equipment optimization.
The benefits of integration can pay off over time. Coordinated engineering services that offer pretested and standards-based measurement, automation, and
information solutions can significantly increase operational performance, quickly reduce errors, and vastly improve the maintenance process. They also make
the instrumentation much simpler for the end user.
Water and wastewater treatment plant operators benefit from this digitalization because they can receive additional process information and achieve tighter
control tolerances, so they can better manage their assets and improve their process.
Building The Business Case For Digital Technology And Integration
Building a business case for digital technology and integration, versus a more basic solution, requires gathering all the figures for the capital expenditure and
then accounting for the operational savings and benefits.
For example, when a standard analog instrument is integrated into a traditional PLC, a plant technician would typically have to walk out to the instrument and
program it locally via the transmitter’s electronics. This can take a significant amount of time to accomplish. With advanced integration and digital outputs, the
necessary data would be recognized when installed in the control system. Additionally, control programming is relatively simple because the system contains a
library of process instructions, profiles, and faceplates.
Integrated systems also reduce technicians’ time in the field. For example, it would be common to send a technician on a 5-mile round trip to use a handheld
tool to perform maintenance or reconfigure an analog meter at a remote pumping station. Multiply that by the expected number of trips annually for each
instrument, and then multiply that number by the number of devices in a distribution system to get a handle on the potential for labor cost savings.
Evaluating Solutions
There are a variety of considerations when evaluating different digital device and integration technologies. The most advanced solutions will offer:
• Adequate documentation that devices and controls integrate seamlessly;
• The option for Ethernet ports, which allows for a reduction in device commissioning; reduction in loop identification, device integration,
and process loop tuning; fastest update of measurement parameters needed for device control; and immediate device recognition as a
network node;
• Pre-engineered add-on profiles/instructions and faceplates that leverage instrumentation intelligence to the control system and through
the enterprise business system about the status of the process itself; and
• In-situ self-verification of calibration.
Self-verification is a critical newer element to integration solutions, and each vendor’s products work differently.
For example, Heartbeat Technology developed by Endress+Hauser embeds diagnostics for continuous monitoring of all relevant internal parameters as well as
mechanical, electromechanical, and electronic components. Diagnostics to detect problems are performed continuously, but an instrument verification can be
done on command from the automation system or with a laptop and Ethernet cable via a web browser, directly from the instrument faceplate or via integrated
WLAN in the display.
These types of diagnostic readings also allow for vastly improved planning, a key to maintaining uninterrupted operations. Water managers will know much
earlier when to clean a magnetic flowmeter’s electrodes or order a new sensor instead of waiting until a problem emerges that can quickly become a crisis.
At the same time, they can avoid unnecessary labor that might be performed during a traditional preventive maintenance schedule that is simply based on a
specific passage of time.
Municipalities should be aware that they may struggle with the overwhelming amount of information that comes with digitalization and integration of flow
measurement and analytical devices. However, the reality is that they can pick and choose which data should be immediately actionable, then add to that list
as they feel comfortable mining for deeper insights.
The ultimate goal of advanced integration technology is to provide water utilities with the best understanding of what’s within their treatment facilities. In turn,
they can provide the best-quality water while operating in the safest and most effective way possible.
Page 11

Feature Article:
Is it time to revamp the SWAN Layers?
Introduction
The SWAN Layers model was one of the first things that was released by the SWAN Forum which started over eight years ago now and it gave the industry a
structure with which the concept of a “Smart Water Industry”. The original SWAN Layers diagram, arguably, was largely based upon the much older Purdue
Model or even the OSI reference model which was invented for ICT systems. The SWAN model provided a simple layered model which everything could be based
upon. This original model was put forward in the white paper “A Layered View of Smart Water Networks” (https://www.swan-forum.com/swan-tools/a-layered-
view/).
The SWAN 5 Layer Model (figure 1) split the structure into 5 building blocks from the physical layer all the way to what is fundamentally data analytics. Extracted
from the original article the different layers can be described as:
The physical layer is comprised, as its name suggests, of the
physical elements enabling the distribution and delivery of
water along the network. Generally speaking, these are the
“wet” components which deal (only with water. Pipes, pumps,
valves, pressure reducing valves (PRVs), reservoirs and delivery
endpoints are all part of the physical layer. These are data-
less elements, that typically perform mechanical, hydraulic or
chemical functions. While the physical layer does not have data
interfaces, it can be controlled using data collected in the next
layer – sensing and control. Although there may be valuable
innovation and design in this layer, any system which is purely
focused on the physical layer is not a part of the data technologies
of the Smart Water Network.
The sensing and control layer is comprised of equipment and
sensors that measure parameters of the water delivery and
distribution (such as flow, pressure, water quality parameters,
reservoir levels, water temperature, acoustic information and
more) and remote-controlled devices enabling to remotely
operate the network (such as remote-controllable pumps, valves,
and pressure-reducers).
In essence, the sensing and control layer is the only interface
between the network operator’s data systems on one side, and
the physical layer on the other side, enabling the connection of
the “smarts” of the Smart Water Network to the real, physical
network. Elements of this layer typically have one “wet” end or
aspect with direct contact or relation to water (such as a valve or
themechanicalendofaflowsensor),andone“dry”datainterface
(such as a valve controller input, or a sensor’s data output).
The collection and communications layer is responsible for discrete data point collection, transmission, and storage. By using two-way
communication channels, commands are then given back to the second layer to instruct sensors and actuators about what data to collect or
which actions to execute. For example, a fixed cable network, radio, cellular, Wi-Fi, and other communication technologies related to data
transfer are all part of this layer.
This is the first “dry” layer, as it only moves data between the sensing and control layer and the higher layers. The data management
and display layer is where data from different sources comes together and may be used by operators. It may be pre-processed, stored,
transferred, and accessed by central systems. Similarly, this is where human operator commands or instructions from higher-level systems
are interpreted into concrete device settings (e.g. changing to a named network configuration may imply switching several pumps on or off,
changing valve states, etc.). This interfaces with the underlying communications infrastructure on one side, and with a human operator or
with other central data systems on the other side.
The data management and display layer is where data from different sources comes together and may be used by operators. It may be pre-
processed, stored, transferred, and accessed by central systems. Similarly, this is where human operator commands or instructions from
higher-level systems are interpreted into concrete device settings (e.g. changing to a named network configuration may imply switching
several pumps on or off, changing valve states, etc.). This interfaces with the underlying communications infrastructure on one side, and
with a human operator or with other central data systems on the other side.
The dashboard applications provided with many SCADA systems (or developed in-house at various water utilities) often fall into this layer,
with some data validation and the display of multiple data streams graphically and in context, etc. Other components in this layer include
data repositories, GIS or network schematic visualisation tools, control room systems with simple alert rules, graphical control interfaces,
Figure 1: Original SWAN 5-Layers Model
Page 12

water balance applications, and fixed-rule feedback automation.
The data fusion and analysis layer brings together raw input data and derives processed knowledge, which was not previously obvious or
trivial from the data as collected. The resulting information may be displayed to a human operator, passed on to further analysis within
the layer, or trigger automatic action by means of the data handling layer (or directly via the communications layer). The value of this
information comes from sifting through the flood of data from multiple samples, data sources, and even data types, to extract high value
information, in the form of alerts on problems, automated responses to system changes, high level summaries, network forecasts, etc.
Components in this layer may include hydraulic modelling systems, network infrastructure monitoring, smart pressure management, smart
(not fixed feedback) pumping or energy optimisation systems, and Decision Support Systems. This layer contains many promising emerging
technologies, en-route to a true “Smart Water Grid.”
The SWAN layers have been very successful in providing an architecture for the Smart Water Industry with the most successful of smart water solutions covering
Layers 2 – 5 and providing a technological solution to the problems that the industry faces.
A case for change
One of the problems that the Smart Water Industry has faced is in the adoption of smart water
technologies mainly focussed around the fact that, in general, the benefits are not fully known
and the business case is generally not well defined and as such the proposals for the adoption
for smart water technologies falls at the first hurdle. On top of this as the SWAN Forum layers are
based upon the technological element then the people factors is often ignored. In a recent blog
by Joel Hagan of I20, entitled “2-Layers Missing” (https://blog.i2owater.com/2-layers-missing) a
variation on the theme of the SWAN Layers has been proposed addressing these weaknesses.
Missing layers are starting to cause problems......The SWAN layers are appealing. It’s a
neat construct.
But there are 2 layers missing, and their absence is leading people in some cases to
do the wrong things. Because data fusion and analytics is at the top, it’s tempting to
conclude that it’s the objective, the thing that everything else builds towards, the end
in itself. It makes people think the more data, the better. There is no reference to a
business objective and the cost/benefit associated with that achieving.
It ignores people and business processes. It suggests that we don’t need to think about
who does what, and what responsibility they each have. And this means that the outputs
of data fusion and analysis are likely either not to get into use at all or to fall out of use.
The 2 missing layers are therefore:
• People and process
• Business objectives
Our favourite example is requests for more frequent dialups by battery powered loggers.
The cost of this is battery life, and battery exchange is often as expensive as the battery
itself, even more so if your loggers don’t have batteries that can be changed in the field.
What no one can explain is why more frequent data delivery is needed, to what use it
will cost-effectively be put, and what anyone will do with the output.
“There is more to water distribution than pipes and valves..” begins the SWAN article.
One might add “There is more to water distribution than data fusion and analysis.”
It’s time to add the missing layers, update the construct and provide a complete picture
and better guidance to the industry.
The discussions when this was proposed also highlighted that within the SWAN Layers we are missing technological advancements such as Artificial Intelligence
and Machine Learning. There is a good argument or these changes however, in my opinion, we have to remember that the SWAN layers are fundamentally a
technological solution and it can certainly be argued that the two new layers are actually part of the business triangle and together form a fundamental part of
each and every layer.
For those who are not aware of the business triangle it is summarised in figure 3. In the triangle the fundamental concept is that any business will not work
without the right balance of Technology, People and Processes. In reality this applies to both businesses in general but aspects of the business including
business initiatives such as “Smart Water.” We’ve seen this historically with a huge amount of instrumentation where early electronic instruments which
weren’t necessarily reliable either due to technological issues caused operators to lose faith in the technology. With a loss of faith in the technology the
business processes surrounding the maintenance of the instrumentation stopped working and the whole adoption of the technology failed. In more recent
years where the technological solution has improved markedly the processes around installation and maintenance have continued to fail and so the full value
od instrumentation has still not been realised in places. This unduly pessimistic and in some places within the water industry the true value of instrumentation
systems are realised but not nearly as much as it could. This is confining things solely to layer 2. The question is what about the other layers.
Figure 2: Modified “7-Layer” SWAN Model
Page 13

Joel Hagan in his blog makes a very good point and the industry is addicted
to the thought of data. However its not necessarily the right data. Personally,
I’ve been a supporter of data and its use but have been fully aware that there
is a data to information ratio and through proper integration data becomes
useful. If we go back to first principles the Smart Water Industry has to be
addressed at the people level and the first task of any company should
be to identify the informational needs through stakeholder engagement
throughout the organisation from CEO to field operative. This will define an
information strategy for the organisation as a whole. Once this is known then
the informational needs will form the data needs and the sources from which
the data must come. This is not only through instrumentation through our
network and treatment systems, but also data from smart water meters, data
from social media sources and a variety of other more disparate data from
unconventional sources.
There are different aspects of each of the areas. Personally, I think the SWAN
Layers cover the structure of the Smart Water Industry beautifully well and
its inception was inspired. It is arguable that developments do need to be
reflected and perhaps the 5th layer – data fusion and analysis could be
rationalised into “Situational Awareness”, “Analytics” or something along
these lines incorporating event management (covering both operations and
the customer), Machine Learning, Artificial Intelligence and other future
developments.
Discussion
Is it time to revamp the SWAN Layers? In my opinion, a tweak maybe but wholesale revamp then my personal answer is no it’s not. We do however need to
recognise that the SWAN Layers are a technological solution and in fact we should recognise that, the technological structure that the SWAN Layers represent,
are actually part of a much wider ecosystem that incorporate both business process and the people element. In order to be successful, the “Smart Water
Industry” must address all three of these components.
This isn’t something new to the Water Industry in fact it has been doing these precise things for many years, especially at Level 1 – the infrastructure layer. Asset
Planning and Management have been putting together capital schemes for many years and these have included all three elements. A similar things has been
happening at both Levels 2 and 3 although arguably less successfully as the true value of instrumentation and communication systems aren’t fully realised and
for the Smart Water Industry to be achieve what it wants to achieve a lot more work is required in these areas before moving on to Levels 4 and 5.
The industry has struggled with the new concepts of the Smart Water Industry and in reality we must all come together and collaborate to realise the value that
it can bring. This will require a focus at each technological layer incorporating both people and processes whilst also addressing the pain points that the industry
has.
Figure 3: The Business Triangle
About the Author
Oliver Grievson is the Editor of WIPAC Monthly, the Executive Director at Water Industry Process Automation & Control, Technical
Lead at Z-Tech Control Systems as well as volunteering as Deputy Chairman of the Sensors for Water Interest Group and also
serves as Chairman of Wastewater Education 501 (c)3. He has over twenty years experience working in the Water Industry in a
number of different roles from Operations Manager, Process Design Engineer as well as acting as a Technical Expert in wastewater
processes and instrumentation and its use in the Smart Water Industry.
Oliver is a Fellow of CIWEM, IES and the IET as well as being a Chartered Environmentalist, Scientist and Water & Environmental
Manager. He regularly discusses both Wastewater Flow and the Smart Water Industry in conferences on an international basis.
He is current serving on committees at both the IWA & the Institute of Measurement & Control on the Digital Transformation of
both the Water Industry and the Utilities Industries more generally
Page 14

Article:
The top 10 real-time water
treatment analytics
Most treatment plants have the instrumentation necessary to be able to create great analytics in real-time, turning data into actionable process insights. Yet
despite all the talk of digital transformation in our industry there are precious few plants where this actually happens. So here are 10 analytics that you could
implement at your plants to kick start your own digital transformation.
The analytics presented here are intended to be calculated either in a plant PLC, for display in the plant control room, or in operational performance monitoring
software for system wide optimisation. Whilst some of the analytics require a lot of maths, it’s all fairly basic stuff.
1 – Production cost (pence/m3)
Let’s start with real-time production cost. This can be a powerful water supply management tool. If you have multiple plants, you can prioritise the plant
producing the cheapest water. It’s also a good diagnostic tool for operators and can provide insights into the financial consequences of treatment adjustments.
Treated water quality always comes first but eliminating overdosing can realise huge opex savings.
Production cost can be calculated by summing the component opex costs. The major opex component is usually chemical dosing. If chemical dose rates are
metered, and chemical pricing is known, you can work out real-time treatment costs. Even if chemicals are not directly metered it’s possible to approximate from
dose rates from pump speed or dry feeder speed for example.
Next, we have power, this needs to be metered and you will know your power supply costs including any peaking factors.
Then we have sludge disposal. To work out a real-time cost for this you need to calculate the solids load based on raw water quality and coagulant dose applied.
Then assuming your solid waste goes to landfill apply a price factor against kg of dried solids produced.
Finally, you can include labour. The simple way to do this is pro-rata plant labour costs. Or you can get more sophisticated by basing it on operator attendance.
Combine all your calculations to give a total cost per m3 of water produced.
This can be taken one step further by normalising for raw water quality allowing a more accurate comparison of treatment plants. It can be taken two steps
further by comparing against predicted costs to treat.
2 – Carbon footprint (kg CO2
/m3
)
This is calculated in a similar way to production costs but rather than applying pound (£) values for chemicals, power and landfill you apply a carbon balance
value. This can be offset by environmental initiatives on the plant e.g. hydrogeneration of power.
3 -THMFP (μg/L or sum ratio of MAVs), HAAFP (μg/L or sum ratio of MAVs)
A basic site-specific version of DBP analytics can be determined using simple UVT measurement of raw water and some laboratory testing. More sophisticated
universal versions can be developed using UV-Vis spectroscopy such as that found in a Compass system. Once relationships are developed, they can be applied
on the plant in real-time on both source water and filtered water prior to chlorination. These parameters can be used for source water selection, treatment
optimisation and real-time process control.
4 - Hydraulic and solids loading rates (m3
/m2
/h and kg/m2
/h)
This one sounds obvious but converting flowrates to hydraulic loading rates makes it easier to define and understand performance limits of the treatment plant.
By using inlet water quality data and the coagulant dose, a solids loading rate can be calculated. This can be used to control clarifier de-sludging, it’s particularly
valuable for membrane plants and it’s a great metric for doing correlation analysis.
5 - Turbidity and/or organics removal (%)
Another seemingly obvious one is percentage removals. It’s amazing that this isn’t used more frequently because it’s particularly valuable for tracking organics
removal. For example, if you have calculated THMFP you should track the removal of this in real-time for optimisation of chemical dosing.
6 - Chlorine Ct values (mg-min/L)
This one is now a compliance requirement in New Zealand so it needs to be calculated on line. The requirements are to calculate the T10 contact time of the
chlorine contact tank based on flow, level, known volume and known baffle factor. This then gets multiplied by the free available chlorine equivalent (FACe)
measured on the outlet of the chlorine contact tank to provide a real-time Ct value.
7 – Chlorine demand (mg/L/min)
Most plants have a chlorine analyser on the inlet and outlet of the chlorine contact tank and yet don’t think to calculate chlorine demand in real-time. Whilst
this delta won’t tell you what the total demand is, it gives a good indication of the efficacy of organics removal on the plant or the presence of inorganic chlorine
demand. Using the calculated contact time in the chlorine contact time normalises for plant flow rate changes.
8 - Cumulative filter turbidity exceedances (%)
In New Zealand and Australia, the regulators require reporting of % exceedances of individual filter turbidity over a month. This can be calculated and presented
to operations staff in real-time during the month as a cumulative figure.
Page 15

9 - Volume calculations (m3
)
Sites often have water storage dams or ponds which have non-linear volume / height relationships with no direct conversion between the two. This can waste
time as available volumes for usage or disposal are calculated by hand or in spreadsheets against SCADA level indicators. Calculating the real-time volume by
applying a non-linear equation saves time and gives greater operational transparency.
10 – Production efficiency and plant losses (%)
Plant production efficiency can be calculated from existing plant flow meters and tank volumes. A rolling average over the previous 24 hours is an effective way
of giving a “real-time” value which considers the impact of batch processes such as clarifier de-sludge and filter backwashing. It’s a good metric for identifying
process issues and for driving improvements in plant efficiency.
So there we have it, 10 analytics that you can apply based on instrumentation that is available for your treatment plant.
About the Authors
Dr Jason Colton completed his PhD in water engineering at Cranfield University in 1996 before working as a Process Engineer in the UK
water industry.. Jason emigrated to New Zealand in 2002. In 2008, he patented the algorithms behind the Compass coagulation control
systems whilst working for Lutra (previously H2ope). This utilises UV-Vis spectroscopy to optimise coagulant dosing by characterising raw
water NOM in real time and producing an ideal coagulant dose for organics removal or minimising filtered water turbidity.
Adapted for WIPAC
This article was originally published on the Lutra website (www.lutra.com) and has been adapted for WIPAC by Tom Lendrem. Senior
Sales Engineer for Process Measurement and Analysis (www.pma.uk.com) who represent Lutra in the UK.
University of Exeter to host pioneering new Centre for Resilience
in Environment, Water and Waste
Research England has announced a £10.5 million investment which will fund a pioneering new collaborative research centre to be hosted at the University
of Exeter – the centre has already received more than £20 million of funding from South West Water. The Centre for Resilience in Environment, Water and
Waste (CREWW) – a joint venture between the University of Exeter and South West Water - will be based on the University’s Streatham Campus. The Centre
will conduct world-leading research into the provision of safe and resilient water services in the UK and overseas. South West Water will play a leading role in
the development and success of the new centre. The Centre will enable SWW to use pioneering new technology, such as robotics or artificial intelligence, to
enhance water efficiency, create better water treatment processes and reduce potential impacts on the natural environment. Central to its focus will be how to
manage natural resources to ensure there is sufficient water to cope with population growth, the pressures of climate change, and improving resilience to the
potentially devastating effects of flood, drought and emerging pollutants. The new centre will accommodate state-of-the-art, specialist laboratory facilities, and
designated space to encourage collaborative research between academics and experts from the water industry.
Crucially, the research will draw on Exeter’s world-leading expertise across a wide range of disciplines to develop innovative new solutions that benefit the
environment, global societies and the economy. Professor Richard Brazier, from the University of Exeter and the Director of CREWW said:
“Building upon our more than 10-year research track-record with South West Water, we will answer a wide range of challenging questions that will help the
water industry deliver environmental improvements whilst safeguarding water supply and improving water treatment.
“Transdisciplinary working will therefore be at the heart of the CREWW, drawing together academics from across the University to work alongside, train, learn
from and engage directly with water industry professionals, for many years to come.”
The innovative research that will be conducted at CREWW will primarily focus on the pressing issues facing the waste and water sectors, nationally and
internationally. These include how to protect drinking water supplies from pollution, protecting water supply networks, and predicting and preventing pollution
from the waste water network. It will also pioneer new research to enhance the safe treatment and disposal of waste water – which includes issues such as
micro-plastics and anti-microbial resistance. The research will be undertaken by academics from Geography, Biosciences, Engineering, Economics, the Medical
School and Psychology, who will work with industry, government and NGO partners. Ed Mitchell, Director of Environment at South West Water said:
“We’re delighted the Centre for Resilience in the Environment, Water and Waste (CREWW) has been awarded funding from Research England.
“Climate change, population growth and increasing customer expectations are key challenges facing the water industry so it’s vital to invest in finding new
innovative and environmentally sustainable solutions.
“South West Water already has a strong partnership with the University of Exeter in this regard. The centre is an exciting development which will bring multiple
environmental benefits through collaborative working and cutting-edge research and innovation.”
The Centre’s funding, through Round 6 of Research England’s flagship capital investment scheme the UK Research Partnership Investment Fund (UKRPIF), was
announced by Universities, Science, Research and Innovation Minister Chris Skidmore at a special event on Wednesday 10th July. It is one of 11 new projects to
receive investment totalling more than £670m. Professor Mark Goodwin, Deputy Vice-Chancellor (External Engagement) at the University of Exeter commented:
“We are delighted to have secured such a significant level of funding for this world-class facility. The Centre will not only provide innovative new solutions to
some of the main challenges of providing safe and resilient water supplies worldwide, but also confirms the University’s pivotal role in leading exciting and
crucial environmental research.”
Page 16

Sizing, selection, and adjusting control valves often causes confusion for process and control system designers. Improper valve application can cause operating
problems for plant staff and waste blower power. Basing the airflow control system design on fundamental principles will improve valve and control system
performance.
TheLawofConservationofEnergyandtheLawofConservationofMassgovernthebehaviorofcontrolvalves.Whenaconceptoraconclusionseemsquestionable,
or unfamiliar technology is being examined, these two fundamental principles must form the basis of the evaluation.
Creating Pressure Differential
The function of any valve is to create a pressure differential between the upstream and downstream piping. If the valve is employed as a shut-off device the
differential is equal to the full upstream pressure. In aeration applications, valves are also used to create the pressure differential required to control airflow
rates – a process known as throttling.
The pressure differential across a valve is dependent on many factors. Fluid properties are significant but are generally outside the control of the system designer.
The mechanical design of the valve and the nominal diameter are also important, and they are amenable to designer selection. In most aeration applications
butterfly valves (BFVs) are used for control, but alternate designs are available.
Regardless of the type of valve, or its size, the restriction to flow can be quantified by the flow coefficient, Cv. This is defined as the gallons per minute of water
flowing through a valve with a pressure differential of 1.0 psi. The greater the flow coefficient the lower the restriction to flow the valve creates. The coefficient
increases as valve diameter increases, or as a given valve moves open. Most valve suppliers publish the Cv data for various diameters and positions as shown in
Figure 1 and Figure 2.
If the conditions of flow are known the airflow rate for a given Cv can be calculated:
Where:
Qs
= airflow rate, SCFM
Cv
= valve flow coefficient from manufacturer’s data, dimensionless
pu
= upstream absolute air pressure, psia
Δpv
= pressure drop (differential) across the valve, psi
SG = specific gravity, dimensionless, = 1.0 for air
Tu
= upstream absolute air temperature, °R
In ISO units, the flow coefficient is expressed as Kv. This is defined as the flow in cubic meters per hour of water at a pressure differential of 1 bar.
It is often necessary to determine the pressure drop for a known flow coefficient, or to determine the flow coefficient
corresponding to a known pressure drop and flow:
These relationships are non-linear. The variation in Cv with position is also nonlinear for most types of valves. This non-
linearity may create problems with control precision if the design or controls aren’t appropriate. There are many assumptions
inherent in any set of fluid flow calculations. Accuracy better than plus or minus 10% should not be expected. This accuracy
is adequate for most systems. Margins of safety and adjustment capabilities should be used in the design to accommodate
uncertainties.
Article:
The Basics of Aeration Control Valves
Shown in Figure 1 is an example of tabulated flow coefficient data for a butterfly valve. Figure 2 is an example of graphical flow coefficient data for a butterfly valve.
Page 17

Bernoulli’s Law in Airflow Control Analysis
In airflow control analysis, Bernoulli’s Law is important. It shows that the total energy in the air stream on both sides of a valve is identical. This is an extension
of the Law of Conservation of Energy. The energy in the moving air consists of three components, as show in Bernoulli’s Law:
Where:
p1,2 = potential energy = static pressure, psi
ρ = density at airflow conditions, lbm/ft3
V1,2 = air velocity, ft/min
Δpf = pressure drop due to friction, psi
Velocity can be readily calculated based on the Law of Conservation of Mass:
The Law of Conservation of Mass shows that on both sides of a valve the velocity is equal unless pipe diameter changes:
Where:
Qa = volumetric flow rate at actual conditions, ACFM (actual ft3/min)
A1,2 = cross sectional area of pipe, ft2
V1,2 = velocity, ft/min
The velocity term in Bernoulli’s Law represents the kinetic energy of the airflow. It is called
dynamic pressure (pd), velocity pressure, or velocity head. In most aeration systems the
dynamic pressure is negligible compared to the static pressure as depicted in Figure 3.
Furthermore, unless there is a change in pipe diameter or a significant change in air density
the velocity and dynamic pressure upstream and downstream of the valve are basically
equal, regardless of valve type.
The blower system must create the total pressure needed to move air through the piping
system and diffusers. The largest component of system pressure results from diffuser
submergence. This static pressure is 80 to 90 percent of the total pressure in most aeration
systems and is essentially constant.
Valve pressure drop is typically the next largest component of blower discharge pressure.
Pressure drops through a BFV or other valve represent a parasitic loss. The frictional
energy from the pressure drop across the valve is converted to heat. In a typical aeration
system the valves share a common distribution header with uniform upstream pressure. The
downstream pressure is nearly identical at all valves because diffuser submergence is identical. Therefore, the value of Δpf is virtually the same for all valves in
a system.
The pressure drop through a valve is used to modulate flow to individual process zones. The valve is adjusted until the airflow through the valve equals the
process demand. The pressure differential equals the available difference between upstream and downstream pressures.
In any system there is pressure drop through distribution piping upstream of the valve and through the piping
and diffusers downstream of the valve. These losses are generally a small part of the total pressure requirement.
In real systems the diffuser pressure drop and piping losses may not be negligible. However, diffuser and piping
losses, like valve throttling, are a function of airflow rate. Differences from tank to tank simply reduce the amount
of throttling required from the valve.
Frictional pressure drops do increase the blower discharge pressure and therefore blower power demand. Energy
optimization includes minimizing valve losses. Minimizing energy with low valve losses must be balanced against
the need to create pressure losses in order to control flow. These conflicting needs can make proper valve sizing
a challenge. Minimizing frictional pressure drop while maintaining controllability necessitates the need to use
realistic air velocities for design as outlined in Figure 4.
Control Valve Characteristics
The characteristics of control valves can be illustrated by examining a simple system with one valve, as shown in Figure 5. The system characteristics are the same
regardless of control valve type. For illustrative purposes the pressure drops through the piping and aeration diffusers will be ignored.
The pressure downstream of the valve, pd1, is established by assuming diffuser submergence of 19 feet, 7 inches, equal to 8.5 psig. Air temperature T1 is 640 °R
Figure 3: Dynamic pressure (velocity head) for a typical aeration application.
Figure 4: Typical design velocity limits for aeration
piping.
Page 18

(180 °F). Pipe diameter is 8 inches nominal Schedule 10 pipe, and a BFV
is used for throttling.
The system is analyzed across an airflow range of 250 SCFM to 1,500 SCFM
(qstd TOTAL). That corresponds to volumetric flow rates downstream of
the BFV between 190 ACFM and 1,100 ACFM (qv TOTAL) and a velocity
range between 500 ft/min and 3,000 ft/min. These are within normal
design limits for 8-inch pipe. The blower is assumed to be a positive
displacement type, and at fixed speed the flow rate is constant regardless
of discharge pressure.
When the valve is throttled the pressure differential obviously changes.
What isn’t obvious from observing the equations is the loss of control at
the upper and lower end of the BFV position range. At positions close to
full open, the pressure drop changes very little as the valve closes. On
the other end of the range, when the valve is nearly closed, very small
position changes create dramatic changes in pressure drop as shown in
Figure 6.
Two conclusions can be drawn from this. The first is that valve travel
should be limited to the middle of the operating range. Control systems
commonly limit travel to between 15 and 70 percent open. These values
are not absolute, of course, and field experience on each system is needed
to establish the most appropriate limits. Avoiding oversized valves and
very low air velocities is important, since that keeps the valve opening
within the controllable region.
The second conclusion is that it is necessary to have accurate control of
position changes. Using actuators with slow operation is suggested, with
60 seconds or more per 90-degree rotation being common. Reducing the
dead band and hysteresis on valve positioners to 1% or less also improves
control.
Motor brakes on electric actuators improve accuracy. Many actuators
have “self-locking” gears which prevent aerodynamic forces on the
valve disc from back-driving and turning the stem when the motor is off.
However, when the motor is powered to reposition the valve and then
power is cut at the set position the motor will continue to spin, acting
like a flywheel. This can drive the valve past the set position and induce
errors and hunting. A brake on the motor engages as soon as power is cut
and stops the valve at the set position.
Many blower control systems maintain a constant discharge pressure.
In these systems the BFV position needed to regulate the basin airflow
rate varies with the set discharge pressure and the corresponding Δp as
depicted in Figure 7. Non-linearity is apparent in this diagram, but if both
the pressure and travel ranges are kept within reasonable limits adequate
control can be maintained. Note that absolute airflow rate precision is not
needed for most aeration applications – slight errors will not materially
affect process performance.
Conclusion
Valves must create pressure drops in order to control airflow by throttling. The relationship can be expressed mathematically using the valve’s Cv. For most
valves the correlation between flow and pressure is non-linear. Despite the non-linearity, proper selection of size and actuator type will provide adequate control
precision.
In the second article of this two-part series, we will examine the interaction of valves in parallel. New types of control valves and their performance will be
compared to the baseline butterfly valve.
Figure 5: Shown is a simple blower system with one valve.
Figure 6: An example of Δp versus air velocity
Figure 7: An example valve position to maintain constant Δp
About the Author
Tom Jenkins is a Principal at Jentech Inc as well as an Adjunct Professor at the University of Wisconsin. He co-founded Energy
Strategies Corporation (ESCOR) in 1984. ESCOR is widely recognized for successfully introducing many original techniques to the
wastewater industry. These include floating control algorithms in lieu of PID, eliminating pressure control of blowers, and variable
speed control of centrifugal aeration blowers. Dresser Roots, a blower and compressor manufacturing company, purchased
ESCOR in 2007. Tom was the Chief Design Engineer at Dresser Roots Wastewater Solutions Group (now part of Howden Roots
LLC). His expertise in aeration and controls covers a variety of process control solutions. This includes dissolved oxygen (DO)
control, Most-Open-Valve (MOV) systems, and blower control.
Page 19

Water utilities the world over need to weather a perfect storm of increasing demand, falling revenues and climate change. While building new assets remains
part of the solution, enhancing the performance of existing assets is more important than ever before.
The growing focus on asset management as a route to providing a high-quality service for utilities’ customers – and meeting quality and environmental regulatory
targets – has been driven to a large extent by the falling cost and increased access to smart sensors and data analytics tools. The rate of change is accelerating
as artificial intelligence (AI) and machine-learning software similarly becomes less expensive and more widely available.
Technology alone, however, is insufficient. The most successful smart asset management and maintenance programmes blend human and technological
excellence. Dynamic maintenance needs to be grounded in the deep institutional knowledge of an asset base that can only come from the people who design,
build and operate it.
The rise of the machines
AI and machine-learning technologies allow water utilities to move beyond the descriptive analytics, which many currently use to understand past incidents and
trends, and shift to predictive analytics, which establish what is likely to happen, and prescriptive analytics, which suggest actions on the basis of the predictions.
The internet of things (IoT) is an important enabler for these approaches. The IoT is made up of connected devices – from simple sensors to smartphones. The
internet’s ubiquity and the availability of cheap sensors make possible ever-increasing cost-efficient gathering of condition and performance data.
Sensors connected via the internet for the purposes of analytics make the visibility of performance cheaper. This gives the flexibility to extend lower-cost
performance monitoring into areas where the level of criticality traditionally would not justify more expensive control and protection systems, but where the
asset failure would not be without cost implications.
These technological advances are helping facilitate new approaches to the ways assets are managed and operated:
Dynamic Preventative Maintenance (DPM) – preventing failures before they occur by using intelligent predictions and dynamic maintenance planning
Prognostic Maintenance Interventions (PMI) – using machine learning, pattern recognition and advanced analytics to optimise, manage and deliver interventions
Data comes at a price
The volume of data these technologies make accessible to a water utility is potentially overwhelming. In addition, there is a cost to capturing, storing and
accessing each data point. So, when developing DPM and PMI strategies, it is vital utilities define the assets and related data that best supports their goals – and
focus on them only.
Failure to achieve this has resulted in data gathering initiatives that cost more than the savings they were expected to yield. This is because of the costs associated
with capturing and storing data and – most importantly – maintaining accurate, up-to-date information.
Like physical assets, asset data has a lifecycle. Around 20 per cent of the cost of gathering asset data comes in the capital phase of the asset’s lifecycle. The
remaining 80 per cent of data costs are generated during the operation and maintenance (O&M) phase of the asset’s lifecycle. This is due in part to the length
of the capital phase compared to the O&M phase, but mostly because the O&M data is live, evolving, and in need of ongoing monitoring, storage and updating.
Understanding the costs associated with the different phases of the asset data lifecycle – and planning data acquisition accordingly – is the cornerstone of
dynamic preventative maintenance. Harvesting data you do not need combined with the risk of using bad data comes, literally, at a price.
After the most significant assets and associated data have been identified, their criticality can be understood. This means focusing on what an asset or process
is intended to do and identifying factors that stop it from performing as required. This information is used to inform measures to mitigate the factors degrading
asset performance, creating a condition- or output-based maintenance regime at the optimum balance between cost, risk and performance.
This root-cause analysis and failure mitigation will allow water utilities to better understand planned and unplanned costs across comparable processes and, if
they differ, understand why. This will give vital insights into the true cost-to-serve.
In reality: Yorkshire Water’s Dynamic Maintenance Planning Programme
Yorkshire Water’s Dynamic Maintenance Planning Programme (DMPP) is one of the first, as well as the largest, programmes of its kind undertaken by a UK water
utility. Yorkshire Water serves five million customers in northern England. The DMPP created an effective predictive maintenance regime covering the utility’s
entire asset base, encompassing 695 water and wastewater treatment works and 83,000 kilometres of water and sewerage pipes.
Central to the programme’s success was the blending of human and technological capabilities. The Asset Information Standards, which dictate how the assets
are recorded and the asset information held, were created with full participation of Yorkshire Water’s O&M teams.
This enabled a collaborative DPM study, producing a condition-based maintenance programme based on failure modes, with O&M buy-in. This approach meant
time and money are focused on ensuring process and asset outputs are maintained.
Innovative use of mobile technology also yielded benefits: iPads with Bluebeam enabled live asset survey findings, and piping and instrumentation diagram
updates, to be uploaded to a dynamic asset database. O&M teams in the field are using mobile devices to access the condition-based maintenance programme
that guides their activities, and to record and upload condition reports, in real-time. Initial indications are a circa 30 per cent decrease in reactive O&M work.
Article:
Moving towards maintenance 4.0
Page 20

Towards maintenance 4.0
DPM and PMI programmes mark a significant step towards maintenance 4.0, the fourth industrial revolution, the shift towards cyber-physical systems. As they
seek to weather the perfect storm, water utilities need to embrace this change. In doing so, it is important that technology is seen only as part of the solution.
To deliver the smartest possible maintenance solutions, O&M teams will need to trust in AI driven programmes. For this to work, the AI platform needs to be
founded on the deep institutional knowledge of water utility design, construction and O&M experts.
Driving a digital transformation: an MD’s perspective
The days of utilities waiting for their customers to call and tell them there is a burst water main, a pressure or a water quality problem are rapidly coming to an
end. Customers, regulators and the media now expect a water utility to know exactly what’s going on, in real-time. Soon it will be the utilities that are proactively
calling their customers to assure them the problem is known, is being addressed and that the system will be back to normal within X minutes.
Also heading for the exit is the utility’s dependence on local knowledge. We all know the salt-of-the-earth operators who have worked on the network for thirty
or even forty years and who know every valve on a first name basis. These guys have served the industry extremely well, but new technologies will dramatically
amplify the amount of data coming into the utility and the manual methods used by these guys will not be able to keep up. Utilities need to build a whole new
level of capability.
It is in this context that everyone at every water industry conference these days seems to be talking about evolving into a digital utility. There are many challenges
surrounding this that the CEO of a utility needs to face:
• While the technologies are seductive, how do I build an effective business case?
• Which technologies do we buy?
• How do I future-proof our utility and not get locked into proprietary systems with short half-lives?
• How do I start this process in a way that ensures I do not compromise the bigger picture and provides the flexibility to gradually and sensibly
build a workable integrated digital architecture?
• The cost of communications and network sensors is coming down and the business case is getting better by the year, but when do we jump
in – now, or do we wait?
• More and more data will be created, but how do we turn all that data into useful actions and knowledge?
• How do I ensure the organisational culture allows us to exploit the potential offered by these technologies?
While there is a lot of debate about exactly what a digital utility looks like, everyone is likely to agree it must include real-time, automatic monitoring of the
utility’s network allied with smart analytics.
Cloud-based Central Event Management (CEM) systems based on data analytics and machine learning can be a sensible way to start. The service enables
early detection of network events and incidents such as leaks, bursts, faulty assets, telemetry and data issues, changes in demand and operational failures.
Aggregating different data types from several sources and learning from previous events, the CEM software continuously improves its predictions.
The first operative example of this is TaKaDu’s Central Event Management which is used by numerous Utilities in Australia (as well as in the US, Europe, and Latin
America).
The system acts as the central management layer for all network events, integrating with any modern IT architecture, and other systems such as enterprise asset
management, work order, GIS and CRM (call centres) and acoustic leak detection.
TaKaDu’s CEM bridges the organisational silos, providing a utility with the opportunity to improve its levels of customer service and reduce costs – the holy grail
of any strategy. With greater visibility, the utility can prioritise jobs more effectively and respond more quickly, know immediately if there is a change in the
configuration of the system or a rapid change in demand, and monitor pressure and the behaviour of pressure relief valves more effectively.
The utility can also detect when and where a leak has occurred, how much water has been lost and monitor the integrity of the pressure districts. With a better
understanding of the relationship between supply and demand, the utility can optimise the capacity of its system over time. Combined with the newly available
water quality sensors, it will be the first, rather than one of the last, to know if there is a drinking water quality problem.
While many utilities are struggling to work out a pathway into the digital future, a data-driven CEM system provides a low-cost, no-regrets entry point that is
easy to implement. The system provides an opportunity to venture into this minefield easily and efficiently without ‘betting the farm’ with a big bang.
Utilities don’t need to wait until they have all the data – they can start with what they have and add the necessary detail. The right system will help the utility
identify the ‘bare’ spots in the data and pinpoint where the data needs to be enhanced.
And it doesn’t stop there – utilities have a larger role to play in making cities more efficient, more sustainable and more liveable. For example, utilities in the US
are already partnering with popular SatNav systems to inform commuters of traffic disruptions caused by infrastructure failures. A CEM system prepares utilities
for their role in supporting smart cities and enables them to respond much more effectively in the event of a major natural disaster.
In summary, CEM systems can improve a utility’s operational efficiency, foster collaboration across the organisation and improve levels of customer service.
Looking ahead, data-driven CEM systems have the potential to make a quantum leap in the levels of customer service delivered by water utility networks. Can
your utility afford not to have one?
Page 21

WIPAC Monthly July 2019

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