Every summer, visitors descend on Elk Rapids in northern Michigan, US, increasing the demands on its wastewater treatment plant (WWTP). Seasonal residents, a cherry processor and a brewery push daily flows to as much as 1.55 million litres, nearly double the winter level. With just two staff members running the plant and a third due to join, managing operational data efficiently is essential.

When Lane Peterson joined the Elk Rapids Public Works Department as lead operator, he found a system built around Excel spreadsheets, separate folders and manual reporting. At his previous facility in Traverse city, he had used Hach WIMS, a data management platform for water and WWTPs.

Peterson turned to Rio, a cloud-based platform developed by Aquatic Informatics, which, like Hach WIMS, is part of the Hach portfolio. He describes it as a more lightweight, mobile and affordable option for a plant of Elk Rapids’ size.

Consolidating operational data

Previously, data from residential flows and the plant’s two industrial contributors were stored separately. Rio brings these records together, allowing Peterson to generate monthly reports, monitor trends and compare industrial and residential loading.

Custom spreadsheets and graphs help him track lift station runtimes, influent loading and seasonal flow variations. Comparing flow rates with pollutant concentrations can also help identify unusual conditions. High flow with low pollutant loading may indicate relatively clean water entering the system, while low flow with high loading can signal a potential discharge requiring investigation.

The platform has also streamlined monthly reporting to Michigan’s MiEnviro portal. Peterson can copy figures from its spreadsheets into the online system and verify them, rather than re-entering data manually. He is also exploring whether pollutant-loading records could support surcharge calculations for industrial contributors.

Managing seasonal changes

Daily flows at the plant can fall to around 760,000–950,000L winter and rise to approximately 1.55 million litres during peak summer weekends. The extended-aeration lagoon system has detention times averaging about 80 hours in summer and up to 110hrs in winter.

The colder months bring a different operational challenge: reduced organic loading can leave the microorganisms responsible for biological treatment with insufficient nutrients. The team therefore avoids wasting activated sludge from November to March, helping to preserve the plant’s treatment capacity.

It also doses the lagoons with nutrient-rich packets supplied by EnviroZyme, containing phosphorus, nitrogen and supplemental microorganisms. Peterson uses Rio to record dosing and monitor retention times as part of the plant’s operational management.

Supporting quality control and staff training

With a new laboratory technician learning the plant’s processes, automated checks have become useful for both training and quality control. The software flags results outside configured limits using red and yellow indicators and can send email alerts when readings require attention.

Peterson has also configured quality assurance and quality control checks for standards and duplicate samples. These help the technician identify potential inconsistencies during data entry, reducing the need for constant supervision while allowing issues to be investigated earlier.

Cloud access means Peterson can receive notifications when he is away from the plant, giving him visibility into results that may require follow-up.

Using operational data to plan upgrades

Without flow meters at its lift stations, Elk Rapids relies on pump runtimes recorded during weekly inspections to monitor system behaviour. Peterson uses these records to look for possible infiltration during rainfall and investigate changes in pump performance.

Longer-than-usual runtimes, for example, may indicate a blockage or additional inflow entering the system. Over time, these observations can help the team identify recurring problems and build an evidence base for infrastructure investment.

Peterson hopes to use the data to support requests to the local council for upgrades, including a new blower or other equipment. The aim is to connect operational observations with a clearer account of when investment is needed and why.

Building a longer-term record

The plant’s next step is to upgrade its supervisory control and data acquisition (SCADA) system, which still runs on Windows 7 and cannot currently integrate with Rio. Once the system is updated, Peterson hopes to import readings at 15-minute intervals, providing greater insight into overnight events and treatment performance.

He also plans to import historical records to strengthen seasonal trend analysis and inform decisions about chemical dosing and plant operations.

For a facility with such a small team, centralised records have implications beyond reporting efficiency. They can help preserve operational knowledge, support staff training and allow colleagues to take over more easily when someone is unavailable.

At Elk Rapids, the shift away from disconnected spreadsheets is helping turn day-to-day measurements into a more consistent record of plant performance — one that can support both immediate operational decisions and longer-term infrastructure planning.

With more than 9,000 monitoring stations, the council is using the platform to improve data quality, streamline field collection and make environmental information more accessible to regulators, researchers, farmers and the wider community.

From hydrology to environmental data management

BOPRC implemented Aquarius in 2014, initially to manage hydrological data including rainfall, groundwater, river levels and flow measurements.

As the council’s monitoring responsibilities expanded, so did its use of the platform. Aquarius now integrates discrete water quality data from LabWare, air quality monitoring data from Mount Maunganui, coastal ecology datasets, water use data and geothermal information.

Bringing these datasets into a central system enables BOPRC to analyse environmental conditions across different datasets and identify trends and relationships that may be difficult to detect when information is managed separately.

This has been relevant to air quality monitoring in Mount Maunganui. The airshed was designated as polluted in 2019 following breaches of New Zealand’s National Environmental Standards for Air Quality for particulate matter (PM10). The council can use monitoring data alongside information on industrial activity and weather conditions to support regulatory decisions and track changes in air quality.

Strengthening data quality and traceability

BOPRC has adopted the National Environmental Monitoring Standards (NEMS) quality coding framework within Aquarius, establishing a consistent approach to environmental data collection, validation and quality assurance.

The platform also connects datasets with supporting metadata, including field measurements, photographs, comments and measurement methods. Audit logs record corrections and changes to metadata, providing a traceable record of how data has been reviewed and updated.

The data review toolbox allows staff to compare raw and corrected datasets while maintaining the audit trail. This supports greater confidence in data used for regulatory decisions, analysis and public reporting.

Digitising field data collection

Since introducing Survey123 for field data capture in December 2020, BOPRC has been able to move information from field sites into its data management workflow more quickly.

Field teams can capture measurements, photographs and contextual observations directly during site visits, reducing reliance on handwritten records and manual transcription. The approach helps minimise input errors while ensuring supporting information is retained alongside the relevant monitoring data.

The council has also developed methods for incorporating qualitative observations into its geothermal monitoring datasets. Observations such as odour and water colour can be recorded as structured information and displayed alongside measured data as time series.

This allows BOPRC to analyse changes in geothermal features alongside parameters such as bore temperatures and fluid chemistry, rather than keeping observational information separately in spreadsheets.

Bringing different forms of environmental knowledge together

BOPRC is also exploring how Mātauranga Māori can be incorporated into its environmental data management practices.

The initiative recognises that environmental monitoring can encompass both quantitative measurements and qualitative, place-based knowledge. The council is investigating ways to represent observations and cultural perspectives within its data frameworks, alongside conventional scientific monitoring.

Expanding access to environmental data

BOPRC uses Aquarius WebPortal to provide public access to quality-assured environmental data. The self-service approach reduces the administrative burden of responding to individual data requests while giving external users direct access to information.

The council has developed reports for specific applications and user groups. Farmers can access information such as soil moisture and other agricultural indicators, while universities and research organisations can use the data for environmental studies.

For BOPRC, making data more accessible also creates a clearer link between environmental monitoring and decision-making by allowing stakeholders to view and interpret information about their local environment.

A central platform for growing monitoring demands

As BOPRC’s monitoring network and environmental responsibilities continue to expand, Aquarius is providing a central infrastructure for managing increasingly diverse environmental datasets.

The integration of measurements, field observations, metadata and supporting documentation gives the council greater control over data quality and traceability, while the web portal extends access beyond internal teams.

What began as a system for managing hydrological data has developed into a broader environmental data platform, supporting BOPRC’s work across water, air, land and geothermal resources.

California utility leverages software and specialist support to maintain regulatory compliance while advancing clean energy goals

As utilities face increasingly complex regulatory requirements alongside ambitious decarbonisation targets, Alameda Municipal Power (AMP) has adopted a technology-driven approach to compliance management that enables its lean workforce to focus on delivering reliable, clean energy.

Serving approximately 70,000 customers in California’s Bay Area, AMP has achieved 100% clean power generation since 2020 — well ahead of the state’s target of reaching carbon-free electricity by 2045. The municipally owned utility relies on a diverse energy mix comprising geothermal, biomass, wind and hydroelectric power.

However, maintaining compliance across multiple regulatory frameworks presents an ongoing challenge for smaller utilities with limited internal resources.

Navigating a complex compliance landscape

AMP is subject to oversight from both the North American Electric Reliability Corporation (NERC) and the Western Electricity Coordinating Council (WECC), requiring continuous monitoring, reporting and documentation across a wide range of operational, cybersecurity and infrastructure standards.

The utility must comply with approximately 30 NERC standards covering areas such as critical infrastructure protection, personnel training, cybersecurity and physical security. In parallel, WECC’s Compliance Monitoring and Enforcement Programme (CMEP) requires participation in reliability assessments, operational coordination and infrastructure protection measures.

For AMP, which operates with around 85–90 employees, maintaining audit readiness while managing day-to-day operations could easily become resource-intensive.

Combining software with specialist expertise

Rather than establishing an in-house compliance department, AMP partnered with compliance services provider Radian Generation, adopting a hybrid model that combines managed compliance services with a dedicated software platform.

The platform acts as a centralised repository for compliance activities, integrating automated deadline reminders, document management, reporting tools and audit evidence tracking. It also supports maintenance scheduling, testing programmes and workflow approvals, helping ensure compliance obligations are addressed systematically.

“We have bi-weekly calls with Andre and his team to review upcoming deadlines and compliance tasks that are all tracked and managed in the software,” said Matthew Detmers, compliance manager at Radian Generation.

“Andre can go into the platform at any time to get a snapshot of where things are at and receive reminders for action needed.”

Beyond software support, Radian’s team oversees regulatory reporting, monitors compliance obligations and prepares documentation for NERC and WECC submissions.

According to Andre Basler, assistant general manager at AMP, the arrangement reduces the administrative burden on internal teams.

“Matthew prepares all the documentation, and I just need to do a quick check to verify and approve. His team then submits NERC and WECC regulatory reports as needed,” Basler added.

Improving efficiency and reducing risk

The partnership has enabled AMP to maintain a strong compliance posture while directing resources towards its core mission of delivering affordable and sustainable electricity.

By centralising compliance processes and automating documentation management, the utility has simplified self-certifications and regulatory reporting while reducing the risk of missed deadlines or incomplete records.

The digital platform also strengthens audit readiness by ensuring evidence and compliance records remain organised, accessible and securely stored.

For AMP, the approach demonstrates how smaller utilities can leverage technology and external expertise to address growing compliance demands without expanding internal headcount.

As regulatory requirements continue to evolve alongside the energy transition, digital compliance platforms are increasingly becoming a critical tool for utilities seeking to balance operational efficiency, risk management and long-term sustainability goals.

The initiative, which marks Blyncsy’s first deployment on the African continent, will monitor approximately 5,000km of roadway using automated computer vision and crowdsourced dashcam imagery to detect critical infrastructure issues in near real time.

The rollout comes as the Western Cape faces mounting pressure from extreme weather events, ageing infrastructure and constrained public budgets. Recent flooding incidents have isolated entire towns, underscoring the urgent need for more resilient and proactive roadway management systems that can keep transport routes operational during climate disruptions.

Blyncsy, part of Bentley’s Asset Analytics portfolio, uses machine learning (ML) to identify damaged guardrails, missing road signs, faulty streetlights, roadway debris and vegetation encroachment. Crucially, the system can also monitor vegetation overgrowth along roadsides — a key factor in maintaining driver visibility and preventing obstructions during the province’s increasingly frequent storm cycles.

The platform can also flag drainage-blocking debris and deteriorating roadside conditions before they escalate into major hazards or costly repairs, enabling authorities to intervene earlier and reduce risks for motorists and surrounding communities.

The technology supports the province’s Roads4U campaign and the Western Cape Infrastructure Framework 2050, both of which prioritise innovation-led infrastructure management and long-term resilience planning. By automating inspections and asset tracking, the department aims to accelerate maintenance response times while improving overall road safety outcomes.

Johannes Neethling, chief engineer for transport infrastructure systems in the Western Cape, said the deployment marks a shift towards preventative infrastructure management.

“This is not just about better data; it is about a proactive commitment to keeping our roads open and our citizens safe,” Neethling said.

He added that the department will now be able to maintain a continuously updated digital inventory of roadside infrastructure assets, enabling maintenance crews to prioritise interventions more efficiently and respond faster during severe weather events.

Mark Pittman, senior director of transportation AI at Bentley Systems, said the partnership demonstrates how transport authorities are increasingly using AI to improve public safety outcomes while modernising critical infrastructure networks.

“As we look toward bringing this technology to more markets worldwide, our goal remains clear: to replace historical precedent with AI-driven insights that reduce risk, lower costs, and ultimately save lives,” Pittman said.

The New York City water supply system delivers drinking water to nearly half the US state’s population, serving over 8.5 million residents in the city and an additional 1 million people in upstate counties. Fed by the Catskill/Delaware System — one of the world’s largest unfiltered surface water networks — the system draws from 19 reservoirs and three controlled lakes with a combined storage capacity of roughly 570 billion gallons.

Reservoir levels are continuously shaped by a delicate balance of inflows, water diversions for supply, and controlled releases to maintain downstream river health. To manage this complexity, the New York City Department of Environmental Protection (NYCDEP) monitors data from 445 sensor sites at 5 minute intervals.

These stations capture key hydrological and water quality indicators such as water level, dissolved oxygen, temperature, pH, and turbidity. The system is further enriched with inputs from the US Geological Survey and the National Weather Service, all consolidated through the Aquarius platform, widely used by water agencies globally for real-time monitoring, modelling, and analysis.

Given the scale and sensitivity of the network, data quality is critical. However, sensor faults, missing values, maintenance interruptions, and measurement anomalies can introduce errors such as sudden spikes or flatlines. Inaccurate data can cascade into flawed forecasts, inefficient operations, and potential water quality risks, making robust quality assurance essential for operational reliability.

To address this, Aquatic Informatics — developer of Aquarius — partnered with NYCDEP to pilot HydroCorrect, a machine learning (ML)-based QA/QC system designed to detect irregularities and either recommend or automate data corrections. The initiative represents a shift in paradigm from manual data cleaning to human oversight of machine-driven correction.

The pilot began with 11 time series across two known problematic sites: the Shandaken Tunnel Portal — frequent spiking due to sensor faults — and the Rondout Effluent Chamber —persistent flatlines indicating sensor failure. At Shandaken, HydroCorrect learned to distinguish true anomalies from recurring noise, reducing false alerts from continuous spikes to only a few flagged events per week. At Rondout, it successfully applied elevation-based rules to identify and correct flatlined readings, replacing them with interpolated trends that better reflected actual system behaviour.

Within two months, NYCDEP gained sufficient confidence in the system to transition from rule-based suggestions to automated corrections for these sites. As performance improved, the pilot expanded to 60 additional sites covering 200 time series, before eventually being rolled out more broadly across the network.

The system also demonstrated value in real-world operational contexts. In one instance, a turbidity spike from 0.5 NTU to 17 NTU triggered an alert above operational thresholds. Investigation revealed that the anomaly coincided with scheduled maintenance, not a true water quality issue. HydroCorrect incorporated this feedback loop, improving its ability to distinguish operational activity from genuine system irregularities across multiple parameters, including turbidity, temperature, and pH.

Before the pilot, NYCDEP teams were inundated with alerts, requiring manual review of each time series — often 5-20 minutes per dataset — to determine whether anomalies reflected real system issues or data errors. At the outset of the pilot, staff still spent several hours per week refining rules and reviewing outputs. As the system learned, this workload dropped dramatically to approximately 20–30 mins/week, freeing staff to focus on higher-value analysis rather than routine validation.

Importantly, the system has begun surfacing previously unnoticed issues, such as instances of negative flow readings. These discoveries prompted further investigation and the development of new rules to better interpret system behaviour.

NYCDEP’s long-term objective is to scale HydroCorrect to approximately 1,000 time series, with a target of automating up to 90% of data corrections. While human oversight remains essential, the emphasis is shifting toward exception-based monitoring, where staff intervene only when genuinely anomalous conditions arise.

“Reducing personnel hours provides cost savings and improving data quality provides better reporting and decision making, but the software is also about reducing mundane work and enabling NYDEPs’ highly skilled workers to perform higher-value and more engaging tasks,” said Aquatic Informatics account manager Dirk Edwards.

Digital transformation is increasingly central to how water utilities manage assets, control costs and maintain service reliability. In Singapore, PUB, the National Water Agency, oversees a potable water network spanning 5,500km and serving more than 1.5 million customers. Proactive leak detection and asset maintenance have thus become critical to strengthening network resilience while minimising operational disruption and unnecessary capital expenditure.

To support these objectives, PUB has deployed a new-generation Transmission Pipe Leak Monitoring (TPLM) system across 200km of large-diameter transmission mains. These critical assets transport high volumes of water under significant pressure, meaning that even minor leaks can lead to substantial water loss and costly damage if not identified early.

The system, EchoShore-TX by Echologics, leverages acoustic hydrophone sensors to detect leaks through both correlation and standalone logging methods. Each installed node — comprising an electronic module, hydrophone, and combined cellular and GPS antenna — collects acoustic data and transmits it to a cloud-based platform at regular intervals. This continuous data flow enables remote monitoring at scale, reducing the need for labour-intensive field inspections while improving visibility across the network.

A defining feature of the system is its use of physics-driven algorithms combined with advanced data processing techniques. Rather than relying solely on conventional AI, this approach integrates physical modelling to enhance the quality and reliability of insights. According to Marcin Kloc, data analyst at Echologics, “Anyone can deploy an AI model and feed it a bunch of data, but it takes real scientific skill to figure out how to use physics and math to transform the data to mine gold out of chaff.”

This integration of physics-based analytics has translated into tangible operational gains. By refining how acoustic data is interpreted, the system reduces background noise and false positives, enabling engineers to focus on high-probability leak events. At the same time, it supports more consistent scaling across deployment sites, allowing PUB to expand monitoring coverage without a proportional increase in analytical workload.

The improvements are evident in the system ‘speed to notification’, a factor in limiting water loss and avoiding escalation. Earlier iterations required four consecutive noise recordings before a leak alert could be triggered, typically resulting in a detection window of 2-3 days. With the introduction of higher-frequency acoustic sampling and spectral data analysis, the updated system has shortened this timeframe to 1-2 days, enabling faster response and reducing the likelihood of secondary damage.

Further enhancements have expanded detection capabilities beyond traditional correlation methods. The introduction of single-channel detection allows the system to identify leaks that do not propagate between sensors. In one instance, this capability enabled the detection of an air-valve leak of less than 5L/min at the sensor location — an issue that would have otherwise gone unnoticed due to the absence of correlatable data.

PUB has emphasised the importance of standardising performance evaluation. A structured set of metrics is used to assess both detection capability and classification accuracy, covering the full spectrum of outcomes from correctly identified leaks to missed events. Two key indicators — leak classification performance and leak sensitivity — are used to measure how effectively the system distinguishes real leaks from normal operational noise and how comprehensively it detects leaks within a given area.

This data-driven framework supports more informed decision-making, enabling PUB to optimise operational resources while maintaining service standards. It also provides a basis for benchmarking performance across different systems and deployments, ensuring accountability and continuous improvement.

The value of early leak detection is significant for large-diameter mains, where replacement costs are high and failures can be disruptive. By identifying and addressing issues at an early stage, utilities can defer capital expenditure, reduce non-revenue water (NRW), and avoid the costs associated with emergency repairs.

PUB’s deployment illustrates how advanced monitoring technologies, underpinned by robust analytics, can deliver measurable returns. Beyond improving operational efficiency, such systems enable utilities to adopt a more predictive approach to asset management, aligning long-term infrastructure planning with immediate performance gains.

Del-Co Water, established in 1969, has grown into one of Ohio’s largest public water systems, serving more than 55,000 customers across eight counties in the US. With multiple raw water sources — including Alum Creek, the Olentangy and Scioto rivers, and regional aquifers — and storage capacity exceeding 2.6 billion gallons, the utility operates at significant scale. This growth has driven the need for more robust data management to support operations and regulatory compliance.

To address these demands, Del-Co implemented the Hach Water Information Management Solution (WIMS), replacing long-standing paper-based processes with a centralised digital platform.

From paper-based workflows to centralised data

Historically, water quality data was recorded manually and stored in physical archives. This created inefficiencies in data retrieval, increased the risk of errors, and limited visibility across teams.

“Before WIMS, we wrote everything on paper and kept it forever; you can imagine boxes and boxes of papers sitting in storage,” said its long-time employee Shannen Green. “The process was time-consuming and prone to errors.”

The transition to WIMS enabled direct data entry through customised bench sheets, reducing duplication and improving data accuracy. Centralised records also provide a clear audit trail and support faster issue identification through access to historical data and operator notes.

Del-Co Water plant manager Damon Dye noted that digital access has improved operational responsiveness: “Operators can now quickly pull up historical data… it is easier to stay on top of things and make quicker, better decisions.”

Automation improves dosing and operational efficiency

A key benefit of the platform is the automation of chemical dosing calculations. Previously performed manually, these calculations are now standardised using built-in formulas, improving both accuracy and efficiency.

The system also generates alerts if process adjustments do not achieve the desired outcome within a defined timeframe, allowing operators to intervene promptly.

This capability is valuable during high-flow periods, when turbidity levels fluctuate due to seasonal factors such as rainfall and snowmelt. By analysing historical data, operators can optimise dosing strategies and maintain water quality.

“In the first year… we used past turbidity and temperature data to determine the required dosage,” Dye said. “What used to take a day now takes 5 minutes.”

Streamlined regulatory reporting

The platform has also simplified compliance with the Ohio Environmental Protection Agency (EPA). Automated report generation enables operators to compile and submit required documentation with minimal manual input.

“As the operators enter data, it creates the monthly report for me… it saves hours and hours a month,” said Dye.

Laboratory workflows have similarly improved. Scheduling, data entry, and validation processes are now integrated, reducing reporting time from several hours to minutes while lowering the risk of input errors.

Managing change and scaling adoption

Initial resistance from operators and laboratory staff required targeted training and support. However, early operational gains helped drive adoption across the organisation.

Del-Co is now working to standardise usage across all treatment plants, with some facilities still transitioning fully from paper-based processes. The utility is also expanding its deployment with cloud-based and mobile capabilities to support field data capture.

Continuous improvement through data and collaboration

Looking ahead, Del-Co aims to further leverage analytics, including graphical dashboards, to enhance visibility of key parameters such as turbidity. The utility is also engaging with industry peers to share best practices and optimise system use.

The adoption of WIMS reflects a broader shift towards digitalisation in water utilities, where data-driven decision-making, automation, and regulatory alignment are becoming operational priorities.

For Del-Co, the transition has delivered measurable gains in efficiency, accuracy, and compliance — positioning the utility to better manage future challenges, including climate variability and evolving regulatory requirements.

As the renewable energy sector scales rapidly, effective portfolio management has become as critical as generation capacity. With solar and battery storage projected to account for 81% of new US electric-generating capacity in 2024, companies such as Sol Systems are refining how they manage increasingly complex asset portfolios.

Sol Systems oversees a 7GW portfolio of clean energy projects across North America, spanning both operational and in-development assets. To manage this scale, the company has prioritised integrated asset management and centralised data oversight, enabling real-time visibility into both financial and operational performance. This approach supports faster response to operational issues, improved asset optimisation, and tailored reporting for a diverse client base that includes commercial customers and landowners.

Managing such a portfolio generates significant volumes of data across development, financing, procurement and operations. Sol Systems uses the Radian Digital platform to centralise and manage information across its US$2bn portfolio, ensuring transparency, accessibility and accountability across stakeholders.

“As you start building a renewable portfolio, you add more projects, have unique investors, and everyone has their custom requirements. Centralising all information into a single source of truth is critical to maintaining data integrity and quality,” said Adam Polis, performance engineering manager at Sol Systems.

The need for centralisation extends beyond performance monitoring. Long-term agreements, such as power purchase agreements spanning decades, introduce complex lifecycle requirements, including scheduled decommissioning and evolving stakeholder responsibilities. Workforce mobility further compounds this challenge, reinforcing the importance of a unified system to track obligations, set alerts and manage tasks across teams.

Data complexity is also heightened by the diversity of equipment across sites. Solar panels and monitoring systems from different vendors often produce inconsistent data formats. Through Application Programming Interfaces (API) integrations, Sol Systems aggregates and standardises this data within a single platform, enabling consistent monitoring and faster fault detection.

The financial implications of outages, whether large-scale or incremental, are a key focus. In 2023, the US recorded 28 weather and climate events exceeding $1bn in losses. While such events are significant, smaller, distributed outages across a portfolio can cumulatively have substantial financial impact.

“Our goal is to measure the impact of each outage and quickly quantify its business impact so we know where to deploy resources,” said Polis.

Using detailed asset mapping and minute-level data analysis, the platform quantifies losses down to individual components. This allows Sol Systems to translate performance issues directly into financial terms, prioritising maintenance based on economic impact rather than operational convenience. Repair workflows are supported by detailed ticketing, ensuring maintenance teams are equipped with the necessary information and resources before arriving on site.

“We do not want our O&M providers inadvertently prioritising lower-impact components. It is not the list that matters; it is the dollars lost based on each individual outage,” Polis added.

Beyond operations, centralised data enhances reporting and compliance. The platform enables rapid generation of both routine and ad hoc reports, supporting investor-specific requirements and near real-time analysis. Queries that would otherwise be resource-intensive can be addressed quickly through pre-integrated datasets and automated calculations.

As Sol Systems continues to expand its operating assets and development pipeline, the ability to unify data across teams and stakeholders remains fundamental. Centralised platforms not only reduce data silos but also enable more informed decision-making, supporting both operational efficiency and long-term portfolio performance.

Located 25 miles outside Washington DC, Loudoun County spans 517 square miles and is one of the fastest-growing counties in the US. Serving the county’s suburban eastern corridor, Loudoun Water delivers drinking water, wastewater and reclaimed water services across more than 1,400 miles of water main to over 87,000 customers, supplying an average of 26 million gallons per day (MGD).

Rapid population growth — up 84% between 2000 and 2010 and a further 35% from 2010-2020 —has intensified pressure on infrastructure originally installed in the 1960s. Ageing mains have increased the risk of breaks, service disruptions and non-revenue water (NRW) losses.

To address these challenges, Loudoun Water embedded Real Water Loss reduction into its 10-year Capital Investment Plan (CIP). Following a review of available technologies, the utility partnered with Echologics to pilot its EchoShore-DX fixed acoustic leak detection system in Sterling Park, a high-break-rate zone.

The sensors were placed on existing fire hydrants roughly 650ft apart to capture the sound profiles of the connected pipelines. The data is uploaded nightly to a secure remote server. The data is correlated between adjacent nodes and a dedicated analyst reviews the data to determine whether the persistent correlated noise (PCN) is actionable.

The network was monitored for 180 days, identifying “invisible” leaks without impacting customers. The installation of the 50 sensors took two days to install. Leak simulations were conducted at five hydrants with equivalent flows of 3-5 gallons per minute.

“Within the first month alone, nine leaks, including six main breaks and three hydrant leaks, were located and repaired,” said Kathleen Whitten, for Loudoun Water. “Having a real person verify the PCN data gives us confidence in the results. This early detection has allowed us to plan repairs, minimising costly emergency scenarios and reducing NRW.”

The pilot delivered measurable results: a 38% reduction in repair costs and improved operational efficiency through planned interventions rather than emergency responses. A total of 14 leak alerts were issued, with 12 confirmed as leaks. Early leak detection also reduced NRW and minimised customer disruption.

Following the pilot, Loudoun Water expanded the programme in phases. As of February 2025, 224 sensors are in operation, with 33 leaks detected. With average repair costs of US$13,000 per main break and $8,000 per leak, the utility reports that capital costs were recovered within three years.

For a fast-growing utility managing ageing infrastructure, continuous acoustic monitoring like the the EchoShore-DX has strengthened asset management, reduced water loss and improved service reliability — positioning Loudoun Water for long-term system resilience.

The City of Kilgore, Texas delivers clean drinking water to about 14,000 residents through an extensive 160-mile distribution network. The system is operated by a team of five water professionals responsible for monitoring and managing flow, pressure, chemical usage, and disinfection residuals across multiple facilities.

Kilgore’s water infrastructure includes a 3.5-million-gallons-per-day (MGD) surface water treatment plant, a 3.5-MGD groundwater treatment plant, seven groundwater wells, a raw water pump station, two water pressure plants, and more than four million gallons of storage capacity. Coordinating water flow and maintaining compliance across this system generates a significant volume of operational data.

Clay Evers, director of public works for the City of Kilgore, oversees water treatment operations and data management. For years, most operational data was recorded manually.

“We have multiple filing cabinets of daily data sheets completed by our operators,” said Evers. “I enter most of the production data into Excel when I have time or need to do a report or troubleshoot a problem.”

Some data was stored digitally through the city’s work order management system, but extracting it proved challenging.

“It is in a SQL database, so you must mine the data — essentially cutting and pasting into spreadsheets to create trend lines,” Evers said. “It’s labour-intensive and requires a certain level of sophistication.”

Technology barriers for small utilities

Like many small utilities, Kilgore faced barriers to adopting new technology.

“Our budgets are small, and our personnel are primarily focused on operations,” Evers explained. “Incorporating technology means changing processes that have been in place for years or even decades. Crossing that technology chasm takes time, training, and proof that the new system is better than the status quo.”

That proof came during a nitrification event in late 2023.

Nitrification event highlights need for better data access

The city experienced difficulty maintaining acceptable chlorine residuals in its distribution system. To investigate, Evers began manually entering historical data into Excel to identify trends.

“By graphing the data, I could see the trend had started about three months earlier,” he said. “It was a real eye-opener. We needed to be analysing our data every day, not after the fact.”

The event ultimately required a free chlorine conversion, involving the removal of ammonia from the treatment process, followed by extensive flushing and additional diagnostic work — an expensive and disruptive response.

“These kinds of events are costly and preventable with modern data management,” Evers said.

Around the same time, Evers began researching how other small utilities were modernising their operations. That was when he received an email from Aquatic Informatics and booked a demo.

Automating daily production data with Rio

Kilgore implemented Rio, Aquatic Informatics’ software platform for regulatory compliance and operational data management.

Prior to Rio, calculating daily water production required manually locating paper records and subtracting meter readings from the previous day — repeated across seven wells.

“It was something we should all know, but it was very labour-intensive,” Evers said. “With Rio, that information is fully automated and available instantly.”

Operators can now view daily, monthly, and soon annual production trends with a single click.

“This helps us identify anomalies, forecast demand, and support conservation efforts,” Evers added.

Streamlining monthly reporting through SCADA integration

Rio also interfaces directly with Kilgore’s SCADA system, automatically calculating minimums, maximums, and averages for parameters such as filter turbidity and chlorine residuals — key inputs for monthly operating reports (MORs).

“The software does the math for us,” said Evers. “I can also compare SCADA data with operator entries and catch errors much more easily.”

Operators enter data either through the Rio mobile app or desktop interface, depending on preference. The mobile app, compatible with smartphones and tablets, has proven especially appealing to younger staff.

Before Rio, MORs took several hours to complete. Working with Aquatic Informatics implementation specialist Rebecca Henzi, Kilgore developed a Rio template that now auto-fills approximately 90% of the required report fields.

“Once a variable is entered into Rio, it flows automatically into reports, dashboards, and trend lines,” Evers said.

Improving visibility and operational efficiency

With centralised data access, Evers can quickly visualise trends in flow, chemical usage, and other operational parameters.

In one instance, Rio helped identify an unseen leak in a chemical line.

“We saw two consecutive days of chemical usage at 75 pounds, when we normally use 150 pounds,” Evers said. “That kind of data was never analysed before. Now it’s hard to miss.”

Over time, the growing historical dataset has become increasingly valuable — not only for daily operations, but also for long-term planning.

“When a consulting engineer asks for five years of operating data to design plant upgrades, having it all readily available is invaluable,” Evers said. “Good data ensures proper sizing and better decisions.”

Supporting long-term planning with fewer resources

With more than 20 years of experience in municipal water, Evers views technology as a way to eliminate unnecessary manual work and focus on strategic planning.

“The ability to quickly retrieve past data helps with maintenance scheduling, budgeting, and planning equipment replacements,” he said.

For Kilgore, Rio has proven that advanced data management is not just for large utilities.

“We have the same regulatory requirements as bigger utilities, but fewer resources,” Evers said.

“Rio is easy to implement, well-priced, and already saving us time. As we use more of its functionality, our capabilities will continue to expand — which is critical for a small utility focused on delivering safe drinking water.”