Water Working Group Framework Best Practices

From OpenCommons
Revision as of 04:13, March 15, 2022 by Pinfold (talk | contribs)
Jump to navigation Jump to search


Utility
Utility
Sectors Utility
Contact Pete Tseronis
Topics
Authors

Ed DavalosOC.jpgKenneth Thompson.jpgScott Pomeroy.jpegDerickLee.jpegDeborah Acosta.jpeg

Nearly every discipline – from sports and advertising to public health and science – relies on data-driven analysis for decision-making. Taglined the “Age of Big Data,” we are becoming more and more reliant on data-driven evidence and analysis for nearly every decision we make. Data is not only becoming more available to the general public, it is also more understandable thanks to increased computing resources and advanced algorithms for analytics.

In utilizing Internet of Things (IoT) technology, utilities are now faced with the daunting task of making sense of the growing stack of data. Some utilities are finding more advanced, efficient methods of managing this data. By leveraging all the data generated at a utility (a truly big data set), utilities are able to provide rapid detection and response to operational events and gain valuable insight into their water distribution or wastewater collection system.

Challenges associated with increasing regulations, increased customer engagement, knowledge transfer for an aging workforce, and demands to do more with less are requiring the industry to change the way it is doing business. The purpose of the Water Blueprint is to demonstrate how utilities are leveraging IoT and Big Data to their advantage in addressing these daunting challenges.

About the Water Working Group

The Water Working Group was formed during the National Institute of Science and Technology (NIST) Energy/Water/Waste Supercluster Workshop in Atlanta, Georgia in March 2017, and comprises team members from Utilities, Technology Providers, Consultants, and Academic Institutions. The group continued to meet via conference calls following the Atlanta Supercluster Workshop to exchange information and share ideas throughout the development of the Water Blueprint document.

The Water Working Group comprises four focus areas: Water Quantity, Water Quality, Data Analytics, and Workforce of the Future. This Best-Practice Framework provides a discussion of the challenges, solutions, technologies, and tools in each of these four areas, as well as example case studies.

The audience and stakeholders for this framework include consumers/customers, City Managers and departments (including O&M, Public Health, etc.), water/wastewater agencies, business and commerce groups, citizen groups, environmental groups, resource agencies, regulatory agencies, and inter-agency groups, Center for Disease Control, etc.

Mission and Vision

The mission of every utility is to provide high-quality, safe water and wastewater services that provide a high level of customer satisfaction, and demonstrate environmental stewardship for their community.

This can be best achieved by harnessing the power of innovative technologies and services, a best-in- class workforce, and a data-driven organization. This Water Best-Practice Framework provides guidance and examples for achieving utilities’ missions and goals.

Strategies

The strategies that came out of the brainstorming sessions and Water Best-Practice Framework development for utilities that desire to create a smart water and wastewater system are captured below:

  • Strategic Plan and System Architecture. Implementing technology solutions before developing a strategic plan and common system architecture rarely leads to a successful smart system program. It is critical to understand where you want to be in the future and the desired level of integration before implementing technology solutions that will end up in silos.
  • Leverage Success. There is an all-too-common theme in the water and wastewater industry to pilot new technology and applications. The industry would move much quicker and reduce the cost of implementation by leveraging systems and applications already demonstrated by others.
  • Cultural Changes. Adopting the use of IoT will require a cultural change for the majority of utilities. This will be similar to the cultural changes made by utilities for safety in the 1980s and security in the early 2000s. Change starts at the top, and senior management endorsement will be critical for success.

Summary of Use Cases and Deliverables

Throughout the discovery phase of the Best-Practice Framework development process, the team identified a large number of successful use cases using IoT to address critical challenges. These use cases were captured and are included here. Some of the critical challenges addressed in the case studies include:

  • Protection of Distribution Water Quality and Public Health
  • Reduction of Non-Revenue Water
  • Reduction of Combined Sewer Overfows (CSOs) in a sewershed
  • Improvement in Water Revenue Collection

Additionally, the team identified unmet challenges that can be addressed through the use of IoT and big data analytics and demonstration projects. These are captured at the end of each section.

Approach

The approach for preparing the Water Best-Practice Framework was a 4-step process:

  • Step 1. The first step was conducted during the 2-day March 2017 workshop in Atlanta. Attendees that were interested in the Water Working Group met over the 2-day period and brainstormed about challenges, stakeholders, and attributes for developing a smart system. The brainstorming sessions covered the areas of water, wastewater, and stormwater. These areas were subdivided into four focus areas: Water Quantity, Water Quality, Data Analytics, and Workforce of the Future. At the end of the workshop, committees were created for each focus area and interested attendees assigned to each.
  • Step 2. The second step was for the group as a whole to conduct monthly calls to accelerate information exchanges and idea sharing. To assist in the information collection process, a Sharepoint site was created for the Water Working Group.
  • Step 3. The third step in developing the Water Best-Practice Framework was to have each focus area leader hold separate calls with their teams to continue developing and refining these sections.
  • Step 4. The last step was to pull the four sections together into a single document in preparation for the NIST Global City Teams Challenge Expo. The document is not 100% complete at this time and remains a work in progress by the Water Working Group.

Common Terms Defined

Advanced Metering Infrastructure (AMI) An architecture for automated, two-way communication between a smart utility meter with an IP address and a utility company.
Automatic Meter Reading (AMR) Technology of automatically collecting consumption, diagnostic, and status data from a water meter and transferring that data to a central database for billing, troubleshooting, and analyzing.
Data Analytics Statistical and mathematical data analysis that clusters, segments, scores, and predicts likely outcomes, compares the present scenario against previous scenarios, or classifies scenarios as anomalous.
Data Platform Centralized computing system for collecting, integrating, and managing large sets of structured and unstructured data from disparate sources.
Energy-Water Nexus The relationship between the water used for energy production, including both electricity and sources of fuel such as oil and natural gas, and the energy consumed to extract, purify, deliver, heat/cool, treat, and dispose of water and wastewater.
Interoperability The ability of computer systems, software, and devices to exchange and make use of data, including those of different manufacturers.
Machine to Machine (M2M) Wireless data communication between machines, generally using networks, especially public wireless networks.
Non-Revenue Water (NRW) Treated drinking water that is lost in the distribution system before it can be delivered to customers.
Open Architecture A type of computer or software architecture that is designed to make adding, upgrading, and swapping components easy (as opposed to closed, proprietary architectures).
Return on investment Ratio of net profit or savings divided by total costs.
Stakeholder A person, group, firm, or agency with an interest or concern in the outcome of a decision or process.
Sustainability The ability to be sustained and supported long term without being harmful to the environment or depleting natural resources.

Available Resources

Additional information on best practices and IoT related to water and wastewater resources can be found in the publication of the following organizations.

  • U.S. EPA Surveillance and Response guidance documents
  • Smart Water Network (SWAN)
  • Smart City Council – Readiness Guide
  • Research foundations – WE&RF, WEF, GWRI, WSAA
  • State Revolving Fund (SRF)

Water Quantity

Potential Stakeholders Desired Contributions to the Solution Desired Achievements/Goals
Consumers/Customers

Regulatory Agencies Resource Agencies Interagency Groups

Water Production and Movement

Storm water – CSO + SSO Meter Accuracy Non-revenue Water – leak detection, theft, inaccurate meters Pressure Management Water Conservation Infrastructure Replacement Hydraulic Modeling/Outage Management Regulatory Compliance Asset Management Long-term Maintenance

Future-proof

24-hour water supply Process improvement to match technology Environmental protection, reduced consumption Sustainability

Problems and Causes

The issues around Water Quantity are different depending on whether you are evaluating the water, wastewater or stormwater system:

  • Water System issues include reliable delivery of clean water, reduction of loss associated with Non-Revenue Water (NRW), ensuring the sustainability of each community’s water supplies.
  • Wastewater System (Sanitary and Combined Sewers) issues include reliable collection and transmission of wastewater to prevent dry weather and wet weather discharges into the environment.
  • Stormwater System issues include Adequately sized collection and transmission system to minimize flooding during extreme wet weather events.

Water System

It is a known fact that our planet’s water supply is finite. There is as much water on earth today as there was yesterday, and as much as there ever will be. However, the human population continues to grow, and along with it the need for more fresh water. Further stressed by aging infrastructures, government mandates, and shrinking budgets, managing our planet’s supply of fresh water continuous to be critical to ongoing economic prosperity and social wellbeing.

You’ve heard the phrase, don’t judge a book by its cover and it’s about quality, not quantity. Well, water quality can have a significant impact on available quantity. If there is plentiful supply, but its integrity is jeopardized in some way, for example by salt water intrusion, pollutants or algal blooms, the availability of clean, drinkable water is significantly reduced.

NRW is defined as treated drinking water that is lost in the distribution system before it can be delivered to customers. Worldwide, more than 32 billion cubic meters of treated water leak from urban water supply systems annually, equivalent to over $18 billion of NRW (source: Itron). Some of these losses, such as leaks are easy to find, but many go undetected, resulting in precious treated water going to waste, lost revenues, and higher production costs. Additional losses associated with theft and poor metering result in lost revenue to the utility. Water losses on the customer side do not affect utility revenue, but they do have a negative impact on sustainable management of precious water resources. An increasing number of water providers are realizing that deploying new technologies such as acoustic leak-sensing across their distribution systems makes both economic and environmental sense. For example, a pipeline leak as small 1/8 inch can lose more than 3,500 gallons per day (gpd) until it is detected and repaired.

Ultimately, the biggest water challenge facing our planet today is the assurance that its most valuable resource can be sustained beyond tomorrow. Just because water resources in a particular area are not in jeopardy today, does not mean they will not be tomorrow. Increasing populations will continue to migrate to, and expect more from, water-rich areas. While Smart City initiatives are finding more efficient ways to sustain the drinking water resource, the demand is ever growing and fresh water supplies will only continue to be strained. The challenge is to ensure they do not become exhausted.

Solutions and Benefits

To meet continually increasing customer expectations, utilities must become more efficient in the way they manage their water resources, handle the demands of their service territory, and engage with their customers. The answer is not to decrease or limit access to fresh water, but rather to increase the efficiency with which water is provided and consumed – decreasing the excess not the access. In other words, to be “resourceful.” We need to understand how and when water is being consumed and/or lost so that decisions can be made today that will positively impact the sustainability of our water resources tomorrow.

This is done through data. But not just data and not just big data. It is through the effective collection of accurate, reliable data and the use of tools to analyze this data. The solutions to managing a community’s water resources include understanding the demands of a utility’s service territory; ensuring sufficient supply is available by more efficiently identifying contributors to NRW (such as system leaks, aging assets, and unauthorized usage); reducing operational expenses and uncovering new revenue streams; and providing customers with access to that same set of information so that they can understand and manage their consumption.

According to the U.S. Environmental Protection Agency (EPA), Water Efficiency is “the use of improved technologies and practices to deliver equal or better service with less water.” The key is access to products and solutions that deliver on that need, and equipping utilities to be able to minimize spending, increase operational efficiencies, and uncover new revenue streams.

Advanced Metering Infrastructure (AMI) and multi-purpose networks, in addition to optimizing the billing process, transform data collected through the system into valuable and actionable intelligence for users across the utility, delivering benefits to the entire organization from billing and customer service to operations, engineering, and distribution, empowering them all to address conservation and resource sustainable opportunities. Delivering the information necessary to make decisions enables a utility to effect change that will have both an immediate and lasting impact on the availability, management, and use of water.

A number of utilities and organizations are already demonstrating their commitment to water efficiency through the use of advanced technologies, implementing solutions that facilitate program objectives. For example, Envision Charlotte in Charlotte, NC has programs in place to encourage the reduction of energy and water consumption in the downtown area of the city (known as Uptown). By bringing awareness to consumption levels through the deployment of advanced technologies capable of collecting hourly interval data, Envision Charlotte is encouraging change in the way energy and water are used and, as a result, showing that businesses can lower the expense of “keeping the lights on.” A key benefit to this program is having more businesses come to the Charlotte area, and therefore more people. This is just one “end” justified by the “means” that demonstrates the power and flexibility of technology capable of satisfying utility challenges around the world.

The City of Madison, WI, thanks to the collection of interval data, was able to establish thresholds for identifying possible customer-side leaks, and then proactively notifying the customer. As a result of the City’s efforts, the threshold for what alerts a possible leak has continually been lowered, or rather fine- tuned, over the past 3 years.

Another example of actuating change within a utility’s operations and customer base is the City of Cleveland, OH. Following the implementation of an AMI, the City has also been able to proactively identify potential customer-side leaks and, in turn, proactively notify their customers. The resulting benefits have been recognized by both the utility and the end customer. Following notification from the utility, Cleveland Water’s customers have the opportunity to minimize the impact to their water bill, and Cleveland Water has seen a significant decrease in the number of bill-related calls to their call center. Furthermore, interval consumption data, coupled with the metered data from district meters, enables utilities to identify potential system losses through District Metering. System losses could be a result of leaks, aging meters, incorrectly sized meters, and/or unauthorized consumption. Having the ability to identify these potential losses prior to rolling a truck results is an immediate, positive impact to the bottom line.

Utilities that are challenged with drought conditions can monitor customer consumption to report on, and enforce, compliance during periods of water restrictions. Knowing when customers are using water, again without having to roll a truck, further decreases operational costs and increases the opportunities to save a valuable resource.

In addition to identifying system losses via the collection of time-synchronized data, with the installation of acoustical leak sensors, a utility can continuously audit the integrity of their distribution system. Knowing when leaks occur, before they damage public or private property, further decreases operational expenses and increases revenue opportunities. With proactive leak detection, utilities are able to reduce the amount of water lost, reduce the cost of repair, and as a result, reduce their NRW percentage.

Case Study: City of North Miami Beach, Florida

Overview: The City of North Miami Beach produces 21 million gallons per day (mgd) of water, delivered to 38,000 endpoints across 25- square-miles of Northern Miami-Dade County. The City’s meter- reading and leak-detection process was labor intensive, time- consuming, costly, and inefficient. Until recently, the City relied on traditional walk-up, manual meter reading, and a leak detection service that visited quarterly to survey areas of its distribution system. Surveyors would visit for 2 weeks per quarter, helping City staff systematically go from one end of the 550-mile pipeline system to the other in 1-mile sections—requiring 1.5 years to get through the city’s 25-square-mile service territory.

IoT Solution: The City is in the process of deploying an Advanced Metering Infrastructure (AMI) solution equipped with leak detection technology and cloud-based analytics. This system will deploy 38,000 communication modules along with 11,000 acoustic leak sensors, automating meter reading and leak detection simultaneously. The AMI system is providing real-time data on customer usage and potential leaks throughout the system, enabling the City to identify leaks within 3 days of occurrence. The result is significant savings in time, staff resources, treated water, and costs.

Benefit/Best Practice: With implementation of the AMI, North Miami Beach is able to enhance customer service, protect revenue, forecast consumption, analyze flow and support district metering by leveraging detailed consumption and meter alerts collected by Itron Analytics. The utility’s customers have access to detailed consumption information through a secure customer web portal so they can better manage their usage, conserve water, and save money.

Case Study: Providence Water Supply Board (PWSB), Rhode Island

Overview: As the largest water utility in Rhode Island, PWSB supplies 60 percent of the state’s drinking water, which includes wholesale distribution and 72,000 retail customer connections across 17 cities and towns. Renowned for its quality, Providence’s water is sourced from surface water reservoirs fed by surrounding watersheds, necessitating a comprehensive management program to ensure purity and sustainability. With distribution system water loss of 11.6 percent, which is comparatively low by national standards, the utility sought to improve water conservation and operational efficiencies.

IoT Solution: PWSB chose automated meter reading (AMR) technology to detect leaks and identify needed repairs in the system. Deployment of 9,400 MLOG sensors and hosted mlogonline began in March 2010 and was substantially complete in May 2012. As of June 1, 2012 the utility was tracking 167 probable leaks. Leaks have been located on copper, lead, and cast iron lines and average about 3 gpm. MLOG deployment also led to the discovery of leaks on gate valves and hydrants, and field technicians have also discovered homeowner water theft and tampering made possible with “jumper” pipes or other types of meter bypasses.

Benefit/Best Practice: Competing priorities require utilities to constantly balance workload and resources. For Providence Water, the top two priorities are water quality and public safety; the third, at least recently, has been leak detection. Now that the utility has access to leak detection data and a trained crew to investigate and repair probable leaks, operations can better optimize its use of personnel and equipment. The utility’s future savings in water production and treatment can in turn be used to fund other necessary infrastructure improvements.

Case Study:Town of Olds, Alberta

Overview: The Town of Olds Public Works and Utilities Department is responsible for maintenance of roads, the water distribution system, and the wastewater treatment plant for a population of just over 8,000. Approximately 10 years ago, the Public Works and Utilities Department determined that the town’s NRW averaged nearly 40 percent, a startlingly high percentage with significant resource and financial implications. In October 2007, the Town formally endorsed a policy to develop and implement a water conservation strategy that included a goal to decrease total municipal water usage by 10 percent by January 2017 compared to 2006 usage.

IoT Solution: In 2010, the Town installed permanent acoustic leak sensors either indoors or outdoors on the water service pipe, usually near a water meter. These strategically placed acoustic sensors analyze sound patterns every day, detecting new, evolving, and pre- existing leaks automatically. A web interface — mlogonline Network Leak Monitoring System — interprets the data and analyzes the recordings and graphically displays all leak sensor locations using GIS and satellite mapping images, highlighting the status and location of leak locations using colored flags. Each “leak flag” prioritizes leaks as either probable, possible, no leak likely or sensor out of status. Over time, an expanding database of historical sensor information has provided a comprehensive condition assessment of the entire water distribution system. In the first 6 months since implementing the system, 21 leaks were repaired – recovering 287,691 cubic meters of water at a revenue savings of $177,336.

Benefit/Best Practice: The leak data analysis has helped the utility to target leak locations much more accurately, and targeted leak probabilities are linked to the GIS mapping interface, providing Town of Olds with a convenient visual representation of the parts of town where most of the leaks are occurring, along with details. This level of leak investigation translates into efficiencies, saving the Town of Olds repair expenses that not only validate their return on investment but also effectively advances their conservation objectives.

Case Study: California American Water, Monterey County

Overview: California American Water (CAW) is responsible for delivering water to Monterey County citizens by pumping more than two-thirds of its supply from the Carmel River watershed. A long-term local and statewide water supply emergency prompted the utility to invest thousands of hours and millions of dollars to protect the wildlife and habitat of the river. These efforts include stemming the loss of water loss through behind-the-meter leaks.

IoT Solution: Working with the Monterey Peninsula Water Management District, CAW set a goal to reduce its water loss from 9.5 percent to 7 percent. After evaluating its options, CAW installed a network of intelligent sensors in October 2008 that detect system leaks by measuring sound vibrations travelling down the pipes. CAW surveyors communicate with the sensors via radio frequency at a minimum of every 30 days, and often gather daily reads that coincide with meter reading. Once a week, the data is consolidated and then seamlessly uploaded to a web interface that ranks and visually maps identified leaks.

Benefit/Best Practice: Soon after deployment, the sensors identified many behind-the-meter (customer-side) leaks and 19 total leaks in the CWA system. The utility continues to reduce its water and revenue losses through this smart technology implementation.

Case Study: Gwinnett County Water Reclamation District, Georgia

Overview: The Gwinnett County WRD has a service area of approximately 68 mgd and 900,000 residents located northeast of Atlanta. While the WRD does not experience significant NRW in its distribution system, TBD. Working with the U.S. EPA, the WRD is implementing an AMI pilot project with the primary focus of using smart water technologies to detect the root causes of NRW due to pipeline leaks and breaks, theft, and/or poor performing meters. Goals of the AMI pilot project include:

  • NRW loss determinations – Number of faulty meters, theft occurrences, and pipeline breaks/leaks
  • Improved system security – Ability to detect and rapidly respond to meter tampering and backflow occurrences
  • Improved system resiliency – Improved response to pipeline breaks
  • Cost Savings – Reduction in water losses from residential side of meter and pipeline loss reductions
  • Value of water savings for both residential customers and Gwinnett County
  • Staff Training – Development of response protocols and classroom training exercise

IoT Solution: Installation of the meters began in May 2017, and data collection will continue for 6-12 months after installation is complete. Technologies and data streams include residential and District Metering Area (DMA) AMI and residential and hydrant pressure sensors from a variety of vendors. Real- time data collected through the meters and sensors is analyzed through cellular-based technologies to identify and reduce NRW.

Benefit/Best Practice: Once completed, data from this pilot study will be shared with the EPA Water Security Division to evaluate its applicability to water security and resiliency. The project is funded by AT&T and Qualcomm for NRW and the EPA for resilience and security studies, with in-kind contributions provided as part of NIST’s Global City Teams Challenge.

Water Quality

Potential Stakeholders Desired Contributions to the Solution Desired Achievements/Goals
Consumers/Customers

City Manager O&M Regulators Environmental Groups Public Health Department / CDC

Water Quality

SCADA and Data Analytics

Regulatory compliance

(safe drinking water) Customer satisfaction PR / customer trust Environmental stewardship Adaptability Optimization

Issues/Problems and Causes

Common water quality issues/problems include contaminants such as Cryptosporidium, Giardia, and E. Coli; discoloration; turbidity; and lead. These water quality issues have a range of causes, both natural and manmade. Contaminants in the source water may be due to any combination of the following:

  • Agricultural runoff
  • Waste from wildlife such as ducks and geese
  • Chemical spills
  • Improper disposal of trash and waste
  • Land clearing and other causes of soil erosion
  • Stormwater runoff (SSO/CSO)

Water quality issues may also result from:

  • Backflow and/or main breaks that introduces contaminants into potable water supply lines
  • Weather and climate change – rainfall, temperature, and drought affect bacteria growth
  • Lead in pipes, solder, and service line components
  • Low chloride levels in areas of the water distribution system, allowing for bacteria growth
  • Low pressure in areas of the water distribution system, which can allow contaminants to seep into pipes through cracks in pipes and joints

Solutions and Benefits

The range of solutions and their associated benefits are equally broad.

  • Source water and distribution line sampling stations – proactively identify contaminant levels of concern. Potential opportunity to automate the stations with sensors and AMI/Smart Cities infrastructure technologies. Multi-head sensor technologies are available today that detect/measure +10 parameters from a single site installation.
  • Remote Chlorine monitoring through sensor and AMI/Smart Cities infrastructure technologies at

critical sampling points in distribution systems could provide a proactive approach to controlling bacterial growth and managing public notifications.

  • Lead level monitoring of source water and critical distribution sampling points can be performed manually or remotely by using sensor and AMI/Smart Cities infrastructure technologies. Cast iron pipe replacement programs, use of only ANSI/NSF 61 certified water meters, valves, couplings and other potable water distribution system components is a common practice for cities to reduce lead levels in their water systems. Some utilities use chemicals to reduce lead or coat pipes to limit lead leaching into potable water.
  • Other Water Quality parameters like pH, Turbidity, etc. can be managed manually or remotely by using sensor and AMI/Smart Cities infrastructure technologies to more frequent and proactive water quality monitoring to protect public drinking water and ensure customer/community satisfaction.
  • Hydraulic modeling and Pressure management can equalize pressure across entire water distribution system reduces main breaks and. AMI/Smart Cities infrastructure technologies can provide timestamped meter readings for water districts or subdivisions to maximize the accuracy of the hydraulic models vs. use of historic usage data. Reducing main breaks preserves water quality by reducing opportunities for the entrance of contamination and promotes conservation of water.
  • Remote/automatic PRV monitoring and control technologies can be used across water systems using that automatically adjust PRV’s to systematically equalize water pressure at critical points and reduce main breaks. AMI/Smart Cities infrastructure technologies can provide the backhaul for these systems. Reducing main breaks preserves water quality by reducing opportunities for the entrance of contamination and promotes conservation of water.
  • Distribution line leak detection sensor technologies coupled with AMI/Smart Cities infrastructure technologies can accurately identify water leaks in distribution lines and reduce main breaks by enabling utility personnel to proactively repair leaks before they break the integrity of the pipe and cause a rupture. Reducing main breaks preserves water quality by reducing opportunities for the entrance of contamination and promotes conservation of water.
  • Use of residential backflow devices on water meters or integrated residential backflow meters is common solution to protect against a siphoning effect occurring at a residential site pulling contaminants back into water distribution systems. Use of Smart Water Meters and AMI/Smart Cities infrastructure technologies can help utilities identify failed backflow devices and provide further protection against this public health threat.
  • Sourcewater level and temperature sensors with AMI/Smart Cities infrastructure technologies can be used to monitor water levels during extreme weather periods to alert cities to associated water quality threats.
  • CSO/SSO monitoring using sensors with AMI/Smart Cities infrastructure technologies can be used to proactively alert city personnel to critical sewer and waste water level conditions to divert flows or prepare for a hazmat situation. CSO/SSO monitoring has proven to reduce regulatory penalties/consent decrees.

Case Study: New York City Department of Environmental Protection (NYCDEP)

Overview: Under a grant from the U.S. EPA Water Security initiative (WSi), the NYCDEP installed a Surveillance and Response System (SRS) with the objective of enhancing existing water quality and real- time online monitoring, as well as improving customer response and consequence management.

IoT Solution: The SRS project included design and installation of 12 online water quality monitoring (OWQM) stations, integration of a consumer complaints system, design and installation of an extensive physical security system and development of a centralized spatial visualization and monitoring system. All data streams from the various components of the SRS are integrated and displayed through an electronic spatial dashboard.

Benefit/Best Practice: Real-time data on water quality, consumer calls, and potential security threats is now available to NYCDEP staff through the SRS dashboard, improving information sharing and response throughout the Department. The SRS also leverages and builds upon existing NYCDEP programs and infrastructure to maximize sustainability and dual-use benefits.

Case Study: Philadelphia Water Department

Overview: Under a grant from the U.S. EPA Water Security initiative (WSi), the NYCDEP installed a Surveillance and Response System (SRS) with the objective of enhancing existing water quality and real- time online monitoring, as well as improving customer response and consequence management. The objective was to integrate multiple forms of surveillance and data streams through ICT to promote early and rapid detection of a water-supply contamination event.

IoT Solution: Major components of the SRS project included design and installation of 20 OWQM stations, integration of a consumer complaints system implemented in Citiworks, design and installation of an extensive physical security system, design and implementation of a centralized spatial visualization and monitoring system, and planning and execution of a full-scale exercise to practice the Consequence Management Plan. The ICT integration of these multiple information streams enables the detection of contamination events not indicated by any individual system component.

Benefit/Best Practice: ICT integration of multiple data streams ensures a safe and secure water supply. The GIS-based dashboard allows the underlying component data streams to be visualized spatially. The ICT system components help to streamline and improve operations under routine conditions, and facilitate the detection of more-routine water quality problems, water main breaks, or source water quality issues. The ICT also eliminates the need for duplicate data entry and manual processing.

Case Study: Dallas Water Utilities

Overview: Dallas is one of four U.S. cities that received a grant from the U.S. EPA Water Security initiative (WSi) to implement a Surveillance and Response System (SRS) demonstration pilot project. The goal of the project was to develop protocols to protect the drinking water system from intentional or accidental contamination and to identify the contamination as early as possible to further protect public health and safety, with the results being used to develop industry best practices for utilities to use across the U.S. The project explored innovative technologies, including various sensors, multiple disparate data sources, data aggregation, and visualization of the data. The data visualization, in particular, used innovative methods to provide operators with spatial and temporal trending of large data sets from all available data sources.

IoT Solution: The SRS project included the design and installation of 16 OWQM stations, 15 of which were connected to the network using 4G cellular connections; integration of a consumer complaints system implemented in SAP; integration of public health data from the Tarrant County Advanced Practice Center; design and installation of an extensive physical security system; design and implementation of a centralized spatial visualization and monitoring system; and planning and execution of a full-scale exercise to practice the Consequence Management Plan.

Benefit/Best Practice: TBD.

Case Study: San Francisco Public Utilities Commission

Overview: San Francisco is one of four U.S. cities that received a grant from the U.S. EPA Water Security initiative (WSi) to implement a Surveillance and Response System (SRS) demonstration pilot project. The purpose of the pilot project was to develop and implement processes to detect a broad spectrum of contaminant classes, achieve spatial coverage within the distribution system, detect contamination in sufficient time for effective response, reliably indicate a contamination incident with a minimum number of false positives, and provide a sustainable architecture to monitor distribution system water quality.

IoT Solution: The SRS project included siting, design, and installation of 10 OWQM stations using the Threat Ensemble Vulnerability Assessment and Sensor Placement Optimization Tool (TEVA-SPOT) hydraulic modeling tool to identify optimal station locations and researching and evaluating multiple OWQM sensors for specific features, reliability, and ease of maintenance. Additional project components included:

  • Design and implementation of a centralized spatial visualization and monitoring dashboard system
  • Further development of the consumer complaints system and integration of the system and the Laboratory Information Management System (LIMS) into the dashboard
  • Procurement of specialized laboratory equipment and development of procedures and associated documentation to decrease response and analysis time, maximize the number of contaminants that could be identified, and increase in-house analytical capabilities  Preparation of police educational awareness videos to enhance understanding of water facilities security requirements by these first responders
  • Development of a rapid query system to enhance the ability to investigate and respond to waterborne contamination and improved cross-jurisdictional coordination during response
  • Planning and execution of a comprehensive full-scale exercise to practice response actions and evaluate the usefulness of the Consequence Management Plan

Benefit/Best Practice: TBD.

Case Study: City of Charlotte, North Carolina

Overview: The City of Charlotte sought a system-wide, full-cycle infrastructure integration and communication solution for its uptown energy and water consumption, air quality, and waste reduction. The resulting program, Envision Charlotte, is a groundbreaking public-private partnership (PPP) supporting the City’s vision to achieve economic growth through environmental sustainability. The program comprises four pillars – Smart Energy Now™, Smart Water Now™, air, and waste – with the ambitious goal of achieving a 20 percent reduction in the use and related costs of energy, water, air, and waste.

IoT Solution: Through Envision Charlotte, building data is monitored, aggregated for the urban core, and reported to building managers, occupants, and the public so they can see a more direct link between their daily business and personal activities and the related impacts on energy and water use. The program has provided a platform for collaboration among government, businesses, and citizens who share Envision Charlotte’s dual goals of economic prosperity and civic sustainability. Smart Water Now™ is centered on smart water grid technologies – connecting with the energy grid – to help the City achieve its goal of a 20 percent reduction in water consumption. That equates to about 53 million gallons of water — or enough to fill 80 Olympic-size pools. Using smart water grid technologies, an automated metering infrastructure (AMI) system was implemented that provides aggregated water consumption information to building managers, occupants, and the public – supporting Charlotte’s goal to be a global model for smart cities. Smart Water Now’s™ integrated virtual data-sharing technologies have maximized community involvement and established a global model for environmental sustainability and measurable community results. These technologies include:

  • Digital grid technologies to display near real-time water data in uptown Charlotte, create broader awareness of the program’s progress, and promote behavioral change to support further progress.
  • Smart meters to capture the water consumption of each building and upload it to the cloud as

encrypted data for network sharing.

  • Video screens in building lobbies to show real-time total water used by business district buildings.
  • Cloud-based aggregation and analyses of water usage to enhance water optimization with utility and smart grid technologies.
  • A network and data-sharing template for future smart city applications.

A Smart Water Now™ web portal was created that enables real-time sharing of data related to community performance in water consumption. The web portal enables building occupants to track the city’s progress on smart phones and online. By providing data in intuitive ways – trending, benchmarking, or correlating with other data sets – program participants are better able to assess how they can build, operate, and live smarter.

Benefit/Best Practice: Envision Charlotte and Smart Water Now™ created measurable improvements in City-wide sustainability and awareness and the related reduction in water costs to the community. Uptown building managers and occupants have access to near real-time water usage, resulting in identification and incentivization of water efficiency measures. The program has also enhanced Charlotte’s image as a progressive city, helping attract new business and strengthen its economic base.

Case Study: Metropolitan Sewer District (MSD) of Greater Cincinnati

Overview: The MSD’s wet-weather assets are spread across its 300-square-mile service area. Minimizing wet weather overflows from its decentralized facilities – many with critical dependencies on other wastewater collection and treatment assets – required an innovative solution that would enable MSD to manage entire watersheds like operators manage a treatment plant. Starting in the late 1980s, the Federal government, through the Clean Water Act, called for the elimination of Sanitary Sewer Overflows (SSOs) and reductions in Combined Sewer Overflow (CSO) discharges. This initiative affected every wastewater system in the country, including the MSD, where the age and design of the system contributed to increased scrutiny and enforcement, as well as heavy civil penalties for noncompliance. In 1999, while MSD had already begun addressing the requirements, costs to customers were a significant factor in entering into negotiations with the U.S. EPA, Department of Justice (DOJ), and State of Ohio to develop an acceptable formal remediation program.

IoT Solution: The MSD worked with a technology consultant to evaluate and implement a distributed system of smart sensors, multi-mode communication through IoT devices, and integration of data streams from disparate sources throughout the watershed – including remote wet-weather storage and treatment facilities, stand-alone flow meters, level sensors, and rain and stream gauges. The resulting Smart Sewer system provides MSD with near real-time visualization of conditions throughout the system and control of critical wet-weather functions, thereby reducing CSO events and associated costs. The smart sewer solution uses real-time data collection and analytics, along with cloud technology, enabling MSD to visualize flow conditions in the entire system in near real time and achieve greater system performance during wet weather. With mobile access and intuitive SCADA screens, operators can navigate the system and immediately access monitoring data and make operational adjustments from any location. An integrated GIS dashboard enables management to have performance data at their fingertips and supports regulatory reporting requirements at the push of a button. With 6,058 SCADA tags, the integrated system is the most sophisticated of its kind.

Benefit/Best Practice: MSD now has watershed-level control of facilities and improved operational decision-making. The data-driven system also enables MSD to increase its readiness before a storm hits through better maintenance, and to improve its performance during wet weather using predictive and alerting algorithms.

  • Connects wet weather assets with other infrastructure systems across the city, enabling MSD to manage its watersheds with the click of a mouse
  • Enhances reliability and readiness before, during and after wet weather events
  • Provides operations staff with the ability to view multiple data streams in real time from a single location
  • Creates actionable information that staff can easily understand and use as the basis for rapid detection and response
  • Allows staff to access key information and make decisions anytime, anywhere and on any device
  • Streamlines regulatory reporting and compliance

Data Analytics

Potential Stakeholders Desired Contributions to the Solution Desired Achievements/Goals
Operator/End User

Customer Service Rep IT Department Resource Conservation Manager Innovation Officer Engineering/Planning Department O&M Staff Tech Providers and Universities Flood Control District

Predictive Maintenance

Adaptability SCADA/Data Analytics Interoperability/Data Platform/Sensors+ Software/Open Architecture Billing + Customer Service Customer Engagement (Social Media) Data Security – Openness/Privacy Cross-Department Integration Sharing of Network Assets

Open architecture data framework

Secure data Accurate data Actionable information Timely data Improved operational awareness

Case Study: Gwinnett County Water Reclamation District, Georgia

Overview: The Gwinnett County WRD has a service area of approximately 68 mgd and 900,000 residents located northeast of Atlanta. While the WRD does not experience significant NRW in its distribution system, TBD. Working with the U.S. EPA, the WRD is implementing an AMI pilot project with the primary focus of using smart water technologies to detect the root causes of NRW due to pipeline leaks and breaks, theft, and/or poor performing meters. Goals of the AMI pilot project include:

  • NRW loss determinations – Number of faulty meters, theft occurrences, and pipeline breaks/leaks
  • Improved system security – Ability to detect and rapidly respond to meter tampering and backflow occurrences
  • Improved system resiliency – Improved response to pipeline breaks
  • Cost Savings – Reduction in water losses from residential side of meter and pipeline loss reductions
  • Value of water savings for both residential customers and Gwinnett County
  • Staff Training – Development of response protocols and classroom training exercise

IoT Solution: Installation of the meters began in May 2017, and data collection will continue for 6-12 months after installation is complete. Technologies and data streams include residential and District Metering Area (DMA) AMI and residential and hydrant pressure sensors from a variety of vendors. Real- time data collected through the meters and sensors is analyzed through cellular-based technologies to identify and reduce NRW.

Benefit/Best Practice: Once completed, data from this pilot study will be shared with the EPA Water Security Division to evaluate its applicability to water security and resiliency. The project is funded by AT&T and Qualcomm for NRW and the EPA for resilience and security studies, with in-kind contributions provided as part of NIST’s Global City Teams Challenge.

Workforce of the Future

Potential Stakeholders Desired Contributions to the Solution Desired Achievements/Goals
HR Department

Operations Manager Universities + VoTech – Curriculum for Data Engineers Executive Staff General Workforce

Transition from Legacy Systems

Aging Workforce Training and Process Improvement Cultural Acceptance SCADA/Data Analytics

Employee satisfaction

Employee retention Well-trained staff Cross training

Issues/Problems and Causes

Under development.

Solutions and Benefits

Under development.

Case Studies

TBD.

Summary of Best Practices

Under development.

Requirements for Implementation

Significant requirements for a City to implement the ideas presented in this Best-Practice Framework include:

  • Trained workforce
  • Funding – bonds, rates, private money
  • City champion in a position of authority
  • Strong business case – quantitative, qualitative, metrics
  • Tiered goals – short-term and long-term
  • Community support / Outreach program
  • Vision for an integrated system, including common architecture
  • Measured baseline
  • Employee cross-training, buy-in, and education (address fear of job loss)
  • Adoption of new business model (managed services, etc.) (NaaS, SaaS)

Reflecting on these city requirements, the major barriers/challenges that cities may face and their possible solution and milestones are summarized below.

Barrier/Challenge Proposed Solution Milestones and Metrics
Funding – services versus rates Create a strong business case

Look at private funding and alternative revenue streams

Short-term (0-12 months) – need financing in place; tiered over time

Demonstrated 3- to 5-year ROI (economic analysis)

Union Objections Emphasize resource reallocation – retraining and education as needed Short- to mid-term (2-4 years)

Negotiated contract

Public Relations and Politics Create a strong business case

Show benefits to public (happy customers/constituents = legacy) Leverage city-to-city competition Economic development Partner with local universities Leverage disasters (Ex: floods, Flint, MI)

Short- to mid-term

Reelection Constituent feedback – 90% customer satisfaction Positive press releases Regional rating system

Commitment to Legacy Systems Create vision for new technology system

Demonstrate strong ROI to justify change

Long-term

Positive ROI

Fear of New Technology Show benefits through demonstration projects Short-term – before implementation
Operations versus IT Staff Ensure open access systems, transparency

Open architecture

90% employee satisfaction (survey)

Proof of safety

Complexity of Systems Embed human intelligence and manual backup options

Open source / open architecture Rollout systematically in steps Provide managed services

Mid- to long-term

Operational success Maintenance savings in FTEs

Skillsets at All Levels Train workforce – need more dataengineers and data scientists

Include cross-function team in decision-making and implementation Provide managed services

Mid- to long-term

Employee retention; < 3% turnover Projected vs. actual costs for managed services

Regulatory Requirements Align internal standards with mission statement

Regulatory relief with Federal agencies

Mid-term

Reduced number of violations and associated costs/fines – pre- vs. post-installation

Lifecycle Costs of IT Systems Decouple hardware and software for staggered maintenance/replacement

Decouple sensing and communication Transition to edge to processing

Long-term

Projected to actual hardware and software costs

Looking Ahead

Under development.

Future topics and areas for growth include collaboration and planning, real-time data collection and sharing, better/actionable and in-house data analytics, interoperability, inter-related sensors, and transition of legacy systems.

Acknowledgements

The Water Working Group would like to acknowledge and thank the following people who contributed their time and expertise to the development of this Best-Practices Framework.

Ken Thompson – Group Lead, Workforce Chair CH2M
Jack Merrell – Water Quantity Chair Itron
John Parks – Water Quality Chair Neptune
Ashu Joshi – Data Analytics Chair Movinture
Rasheed Ahmad City of Atlanta
David Anderson Oracle
Hamid Arbabaraghi HRA
Ven Balaga City of Atlanta
Bob Borzillo Itron
Ed Davalos Motorola
Dominique Davison Planit Impact
Bill Eason Georgia Tech
Ben Easterling AT&T
Michael Flinn City of Atlanta
Landon Franklin AT&T
Sharon Frazier CH2M
John Hall Zmartar LLC
Dryver Huston University of Vermont
Kirk Kalvar
Sudhir Kshirsagar Global Quality Corp
Mary Lasky jhuapl
David Logsdon X
Jeff Lyall AT&T
Carlos Mosqueda Driblet Labs
Subodh Nayar Nayars
Raj Rajagopalan X
Robert Rallo Pacific Northwest National Lab
Senthil Ramakrishnan AT&T
Rodolfo Ruiz Driblet Labs
Brian Skeens CH2M
Michael Son Ecube Labs
Tai Yi Su AECOM
John Teeter Urban Systems
Keisha Thorpe Peachtree City WASA
Bob Watson SAP
Shomari Williams Verizon
Dalei Wu University of Tennessee
Kim Zentz Urbanova / Washington State University