WC138 SeptOct 2024 - Flipbook - Page 34
TECHNOLOGY
AI Makes Waves in the Water Sector
In the not-too-distant future, forecasting, operation, and design of water
projects will be heavily influenced by AI, providing alternatives to planners.
BY GORDON FELLER
RTIFICIAL INTELLIGENCE (AI) is
becoming a valuable tool in water engineering projects, helping to streamline processes, boost efficiency, and support better
decision-making. While AI is widely used in
industries like energy, healthcare, and transportation,
its application in the water sector is still catching up.
How exactly is AI making waves in water engineering? It does so with applications throughout the
project lifecycle: improving operational processes,
reducing costs, and ensuring sustainable water resource management. We sought out insights from Dr.
Daniel B. Oerther, executive director of the American
Academy of Environmental Engineers and Scientists.
We asked him about AI improving existing water-sector digital initiatives, and about the new opportunities that AI will provide.
“AI offers at least immediate improvements to
digital water in its current form,” said Oerther. “Analysis of existing data with AI provides an increased
capability to detect anomalies.”
In Oerther’s view, the gut feeling of experienced
professionals, data visualization, and statistical
analyses are supplemented with AI, “which can offer
yellow flags for further investigation and possible
follow-up as means of identifying problems before
they disrupt system performance.”
Oerther said he believes “AI provides an increased
capacity to offer alternatives for consideration as part
of forecasting, operation, and design. In these two
examples, AI is not replacing human interventions.
Rather, AI provides supplementary information upon
A
Gordon Feller
is a Global Fellow at The Smithsonian
Institution’s Wilson Center. During the past 45
years he’s served as Advisor at the UN’s HQ and,
later, at the World Bank HQ. He was appointed
by Obama/Biden to a U.S. Federal commission
focused on innovations in policy and technologies
established by The U.S. Congress.
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which humans may choose to act.” The water sector
may leverage the benefits of AI as an additional, integrative data source to support human decisions.
IT use in the water sector is already widespread—
with a growing history of success. Oerther offers a
useful example: “forecast models provide decision
support to understand aging infrastructure as well as
trends in user demand from increasingly urbanizing
populations and changing industrial needs, including transportation, energy generation, agriculture,
and manufacturing.” Oerther points to the fact that
forecast models increasingly must consider the realities of changing patterns of weather “which include
both greater maxima and minima of water quantity
(i.e., flood and drought) as well as greater variation
(i.e., more intense rain, more often, or longer periods
of severe drought). Digital water forecasting supports the flexible management of relative risks as an
WAT E R C A N A D A . N E T
