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On the Path to Full NPDES Compliance

Three ways wastewater utilities can leverage technology to eliminate NPDES significant non-compliance (SNC) for good.

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Key Takeaways

  1. Wastewater compliance professionals often manage critical data across a patchwork of paper-based, legacy, and modern data management systems. These fragmented systems introduce risk when managing NPDES compliance because there is no single source of truth.
  2. To make progress on significant non-compliance under NPDES, wastewater utilities will need to adopt better data management tools. These can help cut down on repetitive administrative work, make reporting easier and promote a proactive approach to tackling effluent and compliance schedule violations.
  3. These technologies also present wastewater utilities with the opportunity to move ‘beyond compliance’ by adopting practices that promote resiliency and prepare them for longer-term risks.

Compliance with the National Pollutant Discharge Elimination System (NPDES) permit program touches every aspect of what wastewater utilities do—from the sampling and monitoring regimes they implement, to the way IT departments manage their data, to the way operators calibrate and maintain their equipment.

At the same time, many utilities today continue to struggle to consistently meet the terms of their permits. Between a third and half of all major NPDES dischargers report some kind of violation every year, and in 2018 more than one in five found themselves in significant noncompliance (SNC) with NPDES, garnering hefty penalties and hours of headache-inducing paperwork.

Although the EPA’s National Compliance Initiative and programs like the Wastewater Expedited Settlement Agreement Pilot have made some inroads, noncompliance remains a problem for wastewater utilities and it pays to consider some of the steps operators, compliance managers and IT professionals can take to address it.

Getting to the Root of Significant Noncompliance 

Although effluent discharge and compliance schedule violations are a big problem, according to the EPA more than half of all cases of SNC under NPDES are reporting violations, and 7 out of 10 wastewater SNC violations between 2018-2020 were triggered specifically by a permit holder failing to submit a Discharge Monitoring Report (DMR), the primary method by which dischargers self-report compliance with the conditions of their permits.

National Quarterly DMR Non-Receipt Rate, 2018-2019

Source: EPA Region 1, 2020

What’s driving wastewater’s NPDES reporting problem? At a recent conference, EPA Office of Compliance head David Hindin suggested that everything from regulation complexity to workplace norms could be at play. 

“Common sense and our professional judgment may provide an effective basis upon which to implement environmental compliance programs—except when they don’t,” said Hindin. 

But while it may be easy to blame these failures on human error, the truth is that operators and compliance professionals at wastewater utilities often work in environments that are uniquely stacked against them from a data and reporting perspective.

  • Sampling data is often trapped in log sheets, spreadsheets and SCADA systems, creating data opacity and discouraging proactive data analysis practices.
  • The highly repetitive nature of reporting work itself—often involving the simple act of copying and pasting data from one source to another—creates a breeding ground for basic data entry mistakes.
  • Compliance and reporting processes remain poorly documented, trapped in the heads of one or a handful of individuals at the wastewater utility, or not documented at all. 

This guide lays out steps wastewater utilities can take to avoid these hurdles, do more with the data they already collect, use information technology to build resiliency and cultivate proactive practices, and ultimately set themselves on the path to full compliance under NPDES.

1. Fix the Gaps and Roadblocks in Your Compliance Data Workflows

Over the last two decades, a patchwork of paper-based recordkeeping, legacy software and more modern enterprise software has defined data management practices at wastewater utilities. 

Newer data management software is giving wastewater operators the ability to move beyond this status quo, however progress has been slow.

Although many already do an excellent job of sampling and monitoring, it’s too often the case that those efforts are hindered by workflows that are out of date, hard to work with, or simply nonexistent.

Completing a Discharge Monitoring Report (DMR) for a large wastewater utility often involves wading through a variety of different datasets and software tools, and every bit of friction in that process increases the risk of noncompliance. Specific pain points include:

Outdated Legacy Systems

Many facilities continue to manually enter their data into physical log sheets or SCADA systems, which can cause problems when it comes time to get that data back out and into the hands of a regulator. Additional data entry work, unfriendly user interfaces and slow software can turn tasks that should take minutes into ordeals that can take hours.

Error-Prone Reporting Tasks

Much of the work involved in NPDES compliance and reporting is highly repetitive, often involving copying and pasting data over and over again from spreadsheets and formulas into reports, and creating numerous opportunities for human error. Worse still, manually moving data across documents makes it difficult to identify those errors later, and also opens users to the risk of data duplication or deletion.

Too Many Tools

While paper-based record-keeping can pose problems, loading up on too many software tools can create a situation that is just as painful from a reporting perspective.

“One of the difficulties with diving into the digital world is that you end up having an app for this, and then an app for that, and then an app for that,” points out Adam McKnight, Data Analyst for Halifax Water’s Water Quality Programs. 

Digital transformation should be an important goal for every large wastewater utility, but spreading data across too many dedicated apps can make data management a time-consuming and frustrating experience.

Adopting Tools That Actually Work

While spreadsheets are currently the tool of choice at many wastewater utilities for managing, storing and analyzing compliance data, utilities will have to move past them if they’re to make any progress towards full compliance.

In a recent issue of AWWA Journal, Philadelphia Water Department environmental engineer Tyler C. Bradley points out how over-reliance on spreadsheets can contribute to “human error, lack of reproducibility, and lack of version control. While it is possible to overcome these by using a well-organized worksheet, the work is subject to these errors whenever a different user makes changes.”

The collaborative, cross-functional nature of work at wastewater utilities and the sheer volume of data they’re collecting means that we’ll need new tools that avoid these pitfalls and help users:

Automate Repetitive (and Easy-to-Automate) Tasks

The more repetitive the work, the more important it should be for a wastewater utility to automate it using procured or self-build data management software. Doing so can save administrators hours of busywork and cut down on the probability of human error.

Generate Reports

Compliance reporting and analysis often involves performing calculations on raw data, and doing so manually via spreadsheet can make it difficult for other users to review that work for errors. Entrusting this work to software that generates reports automatically can remove a significant amount of risk from this process.

Eliminate Application Overlap

When possible, utilities should prioritize software that integrates sampling, operations, research and other data and eliminates the need to context switch, learn new tools and create potentially overlapping datasets.

Outflows from LA Sanitation’s Hyperion Water Reclamation Plant 1-Mile Outfall (Photo credit: Google Earth)

2. Use Data to Move From Reactive to Proactive Problem Solving

While NPDES reporting violations are a problem, they’re not the only source of significant noncompliance at wastewater utilities. 

Even if better data management practices can make submitting DMRs a less painful process, effluent limit exceedances and compliance schedule violations will continue to be a serious problem, leading to operational headaches, EPA fines and poorer public and environmental health outcomes.

When implementing technologies that make it easier to report compliance and violations, it pays to consider how those same technologies can help wastewater utilities avoid violations in the first place—specifically by transforming wastewater problem-solving from a reactive process to a data-driven, proactive one. Specific ways that wastewater utilities can do this include:

Improving Remote Monitoring Capabilities

COVID-19 lockdowns across the country drove home the reality that the future of work is distributed and that the ability to access our work remotely is key to resilience. 

Thankfully the water industry is already ahead of the curve in this respect: many utilities already manage thousands of infrastructure assets remotely using sensors, controllers and transmitters. Building on that success and bringing remote monitoring data into a single, easily accessible system can help utilities:

    • Cut down on travel and site visits
    • Implement more accurate notification and alert systems
    • Shorten response times
    • Scale new operations quickly
    • Respond to unexpected staffing shortages 

Increasing Access to Real-Time Data

Being able to monitor water quality, energy consumption, pressure levels and myriad other data points in real time also gives operators, engineers and compliance workers the opportunity to spot and address new trends before they become problems. Making sure those real-time figures are accessible via user-friendly console or dashboard will be increasingly important as wastewater utilities consolidate and build out their data management systems.

Adopting Tools That Make It Easier to Share and Collaborate

Wastewater utilities don’t need algorithms and complex math to use data to tackle compliance challenges. In many cases, finding ways to make sure data is available to the right people at the right time can be just as important.

That’s why tools that create opportunities for communication and data sharing between compliance, operations, engineering and all other business units within a wastewater utility are also crucial. For larger organizations, that often means centralizing data in a universal, easy-to-access system that provides a single source of truth.

3. Aim Beyond Compliance

Wastewater treatment facilities aren’t always perfectly designed, and the world outside of them is subject to constant change. Trends that could impact the ability of wastewater facilities to stay compliant and successful include:

  • Urbanization and other fluctuations in population and flow
  • Shifts in the needs of local industry
  • The emergence of newly-regulated contaminants like PFAS
  • Changing regulations and permit requirements
  • Maintenance, design and equipment challenges
  • Increasing budgetary constraints 

Although it’s hard to beat compliance when it comes to north stars for wastewater utilities, if organizations are to truly succeed in an increasingly unpredictable future, they’ll have to build systems that account for the unexpected, build resilience and move beyond compliance as the sole goal.

Turn Data Graveyards Into Data Mines

The amount of data generated by wastewater treatment plants has increased exponentially over the last few decades. 

One 2014 study found that a single large wastewater treatment plant (0.8-3 million population served) can generate upwards of 30,000 data points, encompassing everything from sampling data to GPS coordinates, call logs, field notes and more. 

“Plant operators have an overwhelming stream of data at their hands, which is very difficult to process and analyze in a timely enough fashion to allow for better understanding or proper decision-making,” writes Lluís Corominas, a researcher at the Catalan Institute for Water Research. 

To better understand and predict noncompliance in our wastewater treatment systems, we’ll have to move from seeing these vast databases as a liability—or as Corominas puts it, “data graveyards”—to a valuable asset that can be mined for actionable knowledge. 

Leverage Machine Learning and Other Data Science Techniques

One benefit of adopting the data management practices and tools discussed earlier is that they open the door to more sophisticated forms of monitoring and analysis that ultimately allow utilities to do more with what data that they already have. 

Machine learning methods that determine patterns within large datasets are one such technique that is already showing promise in the urban water sector.

  • A recent pilot of machine learning tools for predictive control and advanced analytics at Singapore’s Ulu Pandan Water Reclamation Plant helped operators achieve a 15% reduction in aeration energy usage compared to conventional techniques. 
  • Similar techniques have recently been used to analyse wastewater data to determine the scale of local COVID-19 outbreaks in China and Canada
  • In 2018, researchers from Stanford also demonstrated how machine learning techniques could be used to double the number of Clean Water Act violations detected without increasing the number of inspections.

While many of these tools are still in their infancy, there’s no question that there are valuable insights to be gained from wastewater data, and that the sooner utilities can store, organize and centralize this data, the better.

How Klir Can Help

Klir is a single, unified operating system for water, pulling every aspect of wastewater management—including compliance, sampling and more—into an easy to use dashboard. Learn more about how Klir can cut down on administration and record-keeping work, create new opportunities for collaboration, and provide a level of system-wide visibility unmatched by other water data management systems.

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