3 Challenges to Collecting Water Quality Data

3 Challenges to Collecting Water Quality Data
There are many challenges to collecting water quality data. Investing in versatile equipment that can be used in an array of applications can help combat the ever-changing regulations.

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Collecting and analyzing water quality data helps ensure a water system or treatment facility operates properly and meets national standards. However, maintaining data integrity isn’t without challenges. Here, we examine some of the most common problems associated with collecting water quality data as identified by industry professionals. 

1.     Changing regulations

Even the most successful program can be blindsided by new legislature and changing regulations. In an instant, your workload can change or your equipment can become outdated. In a recent webinar presented by YSI, which addressed the challenges of collecting water quality data, presenters used the EPA’s nutrient reduction program as an example, stating that some groups are now being asked to monitor nitrate levels. New regulations can be expensive to implement, especially if a utility or water treatment plant is using older monitoring equipment and software.

Tim Suddarth, chief operator at the 2 mgd (average) City of Portland, Tenn., water treatment plant, which serves a population of 20,000, says regulation changes can greatly affect a budget.

“For a small utility, $5,000 or $6,000 is a big part of my budget,” he says.

To combat this ever-changing landscape, YSI recommends investing in versatile equipment that can be used in an array of applications. For instance, application-specific instruments are now being consolidated into one or two systems. 

2.     Incomplete data

Whether from instrument failure, data gaps or even human error, data is sometimes missing or incomplete. This is a common, age-old complaint for water data collection. Combating instrument problems is probably easier than removing human error. YSI states that in the past three to five years, smart sensor technology has helped erase some data inconsistencies. 

However, slight variances still occur when different operators perform the same task, which was a common response when the question was posed to the LinkedIn Water Treatment Industry group. 

“The biggest problem I have seen is that each operator will perform sampling and testing in their own way with slight, or not so slight, deviations from the manufacturer’s or employer’s instructions,” says James Glenn, drinking water plant operator with the City of Waco, Texas. “These range from procedure shortcuts to speeding through sample processing.” 

Suddarth, whose plant has won several best tasting water competitions, says he commonly sees this situation on color-change tests, such as alkalinity, where one operator might read the results differently than another. 

“Everybody has their own intricacies on how they do things,” he says. 

3.     Funding

Funding is really the key to everything. Remove money from the equation, and organizations could readily adapt to changing regulations, instrument failures, data gaps and more. The issue is sometimes more exaggerated for small municipalities.

“It gets frustrating because I know the programs and technology exists, but the funding for a system as small as ours is hard to come by,” Suddarth says. “Contracting out the heavier maintenance has really helped out.” 

To combat shrinking budgets and revenue issues in general, YSI recommends instruments such as smart sensors that offer concurrent calibration. These instruments increase efficiency and lower the cost of ownership. It’s not an answer to funding challenges, but increased efficiency can add up to savings over the long run. 

Which of these challenges have you encountered? How has your organization worked to overcome them?



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