Investigations of operational difficulty: Uncovering the drivers of persistent noncompliance at water treatment facilities
Date
2024-12
Authors
Ten Pas, Derek
Major Professor
Advisor
Ikuma, Kaoru
Liu, Lu
Poleacovschi, Cristina
Committee Member
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Abstract
Water treatment plants produce clean, potable water for communities around the United
States every day. When water treatment plants consistently operate well, their operations occur
mostly in the background, unnoticed by the average consumer. However, drinking water
treatment plant operation profoundly affects how consumers experience their drinking water. To
protect consumers, the U.S. government provides regulations that guide water treatment plant
design and operation. Despite these regulations, utilities serving small, rural, and low-income
communities are vulnerable to poor drinking water quality, especially in Alaska. Vulnerabilities
experienced by water treatment plants in the U.S. can be imposed by a variety of factors such as
the poor availability of quality source water, or the remote location of rural treatment plants, but
sometimes these vulnerabilities are due to operational challenges occurring at the water treatment
plant. The overall goal of this work was to determine the key drivers behind operational
difficulty at water treatment plants.
In Chapter 2, operational difficulty is observed on the local scale through tap water
sampling in an Alaskan Native Community. Results from these analyses reveal that water
treatment plant operation is exposing the community to an enhanced risk of microbial
contamination as well as lead and copper exposure. pH and chlorine, the two parameters the
water treatment plant has the most control over, were the only tested analytes that measured
outside of recommended ranges. Measured pH was consistently slightly acidic, and most
collected samples exhibited serious corrosion potential. Additionally, measured free chlorine
residuals were lower than the common minimum recommended residual of 0.20 mg/L Cl2. This
community has historically struggled with water operator recruitment and retention, as well as
Safe Drinking Water Act violations. From conversations with city staff, our results match
intentional operational decisions made at the water treatment plant by the lead water operator.
In Chapter 3, the scope of observation is expanded to an at-large analysis of facility-level
datasets comprised of sociodemographic and operational data from Alaska, Illinois, Missouri,
and Iowa. In this analysis, a machine learning model is tasked to predict whether a utility is a
persistent violator of monitoring and reporting violations, that is, whether a utility has had an
active monitoring and reporting violation for over 50% of the time over the previous 3 years.
Once the model performed reliably, an analysis of feature importance was used to interpret the
model’s predictions, and in turn highlight possible drivers of operational difficulty at water
treatment plants. Results of our analysis indicate that communities subject to social
vulnerabilities of small populations, poverty, and racial diversity are more likely to be served by
a water treatment plant experiencing operational difficulty. Additional operational vulnerabilities
also emerge. Water treatment plants that employ under-certified operators or are inadequately
staffed are more likely to be persistent violators, struggling with water treatment plant operation.
Overall, the results of this research emphasize the important role that water operators play
in the success of drinking water treatment. In particular, this thesis emphasizes the importance of
adequate staffing and certification of water treatment operators. This is observed locally in
Unalakleet, but also broadly on the national scale. This information is extremely relevant
considering an impending retirement wave of water treatment operators, and it serves as a call to
action for more resources to be directed towards the improvement of recruitment and retention
strategies of water treatment staff.
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