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Provision of safe drinking water by water utilities is challenged by disturbances to water quality that have become increasingly frequent due to global changes and anthropogenic impacts. Many water utilities are turning to adaptable and flexible strategies to allow for resilient management of drinking water supplies. The success of resilience-based management depends on, and is enabled by, positive relationships with the public. To understand how relationships between managers and communities spill over to in-home drinking water behavior, we examined the role of trust, risk perceptions, salience of drinking water, and water quality evaluations in the choice of in-home drinking water sources for a population in Roanoke Virginia. Using survey data, our study characterized patterns of in-home drinking water behavior and explored related perceptions to determine if residents’ perceptions of their water and the municipal water utility could be intuited from this behavior. We characterized drinking water behavior using a hierarchical cluster analysis and highlighted the importance of studying a range of drinking water patterns. Through analyses of variance, we found that people who drink more tap water have higher trust in their water managers, evaluate water quality more favorably, have lower risk perceptions, and pay less attention to changes in their tap water. Utility managers may gauge information about aspects of their relationships with communities by examining drinking water behavior, which can be used to inform their future interactions with the public, with the goal of increasing resilience and adaptability to external water supply threats.
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Application of Clustering Approach for Risk Assessment of Drinking Water Facilities Worldwide
United Nations recognized access to safe drinking water as a human right, yet many countries in the developing world lack access to potable water. Recurrent incidences of water-borne illnesses have a devastating effect on the morale and personal well-being of many people living in developing countries, contrasting the achievement of the UN’s objective. Qualitative and semi-quantitative approaches used for risk assessment are often ineffective, time-consuming, and do not discern the risk due to ingestion of unsafe drinking water at the global scale. This research utilizes a global dataset of drinking water facilities to evaluate the risks using a clustering approach. Extensive data analysis involving predetermined risk thresholds, the exceedance of which indicates the potential adverse risk. These risk-thresholds are based on the JMP Service Ladder, which effectively utilizes density-based spatial clustering of applications. Risk analysis of 132 datasets was conducted to designate the risk categories ranging from low, medium, and high-risk. Of the dataset analyzed, 90 areas were designated as a low-risk category while 42 were medium-risk. Overall, the clustering approach is an excellent tool to analyze a large dataset for risk assessment which will help the potential stakeholder, including the water utility manager, to assess the potential risk due to declining water quality quickly. Additionally, the clustering approach can be further harnessed for better data visualization, long-term performance evaluation of water utility, and real-time drinking water quality monitoring.
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- Award ID(s):
- 1832536
- PAR ID:
- 10358972
- Date Published:
- Journal Name:
- Proceedings of the 39th IAHR World Congress
- Page Range / eLocation ID:
- 3574 to 3579
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.3850/iahr-39wc2521711920221253
