A Systems Approach to Managing the Urban Infrastructure Grid
NSF-sponsored workshop (grant CBET 1929869)
September 9-10, Cincinnati OH
The National Science Foundation funded a series of workshops on Sustainable Urban Systems (SUS), and this workshop is part of the series. It took place in Cincinnati, OH, on September 9-10 of 2019. The main objective of the workshop was to bring together a diverse group of experts representing different stakeholder groups and institutions, all of whom had interest in urban sustainability. This document provides a report of discussions that took place during the workshop, along with a set of recommendations for future research.
Modern cities are challenged by climate change, growing population, shrinking and polluted natural systems (e.g. streams, wetlands), and rapidly ageing and outdated infrastructure. These challenges manifest themselves in a wide range of problems from flash flooding to frequent power failures and public health issues due to lack of clean water for drinking and recreation. Such events expose the fault lines of urban infrastructure management. Perhaps more importantly, they also reveal the complex and interconnected nature of engineered, natural and social systems that form the fabric of modern cities.
These systems can be conceptualized as a network of networks, or Urban Multiplex, whose subsystems include the power grid and transportation network, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams, intertwined with the socioeconomic and public health sectors. Yet, traditional urban infrastructure management approaches deconstruct this complex system along specific business and political lines, and manage its components separately, often as if they were not related. The traditional modus operandi remains in place because urban infrastructure development and management is overseen by a multitude of organizations and facilities that operate largely independently from one another to meet their own requirements, and often have conflicting interests. The result is cascading failures across the Urban Multiplex, with catastrophic impacts on human and environmental health.
The objective of the proposed workshop was to convene multi-disciplinary experts from utilities, private industry, academia, non-profits, and federal transportation, environmental and public health authorities to systematically address the interconnections between sub-systems of the Urban Multiplex and to identify potential pathways for cascading catastrophic failures and their impacts beyond infrastructure. The participants worked to advance a clearer understanding of complexity of the Urban Multiplex, and to develop a vision and a roadmap towards its sustainable management for improved environmental sustainability and human health.
The workshop consisted of a series of presentations followed by general and breakout group discussions on three main topics: (1) monitoring and data interoperability; (2) analysis and modeling for management and operations control; (3) synthesis towards complexity. The fourth session was dedicated to outlining recommendations for future research. The structure of this report reflects that of the workshop.
The group has made several recommendations for future research:
- Urban infrastructure should be treated as a complex system of systems
- There is a need to address urban sustainability problems over different time scales, from real-time to long term planning, to support interconnected infrastructures that serve urban systems
- Any analytical capabilities for urban sustainability should be intertwined with continuously streaming data to allow for flexibility and on-the-fly control. Detailed city simulations should be developed and used to explore a variety of resilience adoption strategies
- Human and institutional dimensions in urban areas should be better understood, including feedback loops across the urban multiplex
- Technological solutions to urban sustainability challenges should be balanced with potential impacts to different communities
- The socio-economic, as well as environmental, impacts of green technologies should be better understood
Session 1. Monitoring and Data Interoperability
This session showcased a series of presentations and discussions of existing datasets and standards pertaining to urban infrastructure and urban public health indicators. The presentations were multi-sectoral in nature, addressing water issues, public health, and traffic. Each of these sectors could benefit from data from the other; e.g., public health is a function of traffic (air quality) and water quality.
From the discipline specific presentations, breakout discussions identified some common themes across the distinct urban sectors. The highlights include the following:
Data should be thought of as part of our infrastructure much like highways, as many human decisions in the urban multiplex are driven by data, e.g. travel routes, mass transit delays, drinking water-quality reporting by utilities, etc. We have most of the cyber infrastructure we need, but interoperability is not there yet. There also may be a need to develop the expectation that users pay for data, just as we pay for many other urban services, but the value of data must be clearly articulated to data users and the broader community that supports data infrastructure. Communication of available data resources should be broad and include those beyond the typical user community. Such communication could lead to innovative applications of existing data.
Standardization of data across sectors seems to be an insurmountable and unnecessary task. Current cyberinfrastructure seems adequate for integrating data across sectors as long as those data are (1) accessible and (2) contain necessary metadata to describe the data and methods used to create the data. Workflows for data manipulation should be documented and reproducible.
Maintaining continuity of data often is a challenge, especially for data collected as a part of a relatively short-term project. Moreover, political will to fund ongoing data collection often is missing. In addition, maintenance of existing data can be a challenge so that resources need to be available to support data repositories.
There are known data gaps, and unidentified data gaps within the urban systems. Managers should be prepared to answer questions related to future data needs and to prioritize those needs. As new data-collection efforts are initiated, there is a need to ensure that data are connected across domains so that data are interoperable. In general, the cyberinfrastructure exists to support most foreseeable data collection and sharing.
In addition to data gaps, all data contain some level of error. Allowable data uncertainty varies across sectors, so acceptable uncertainty needs to be articulated as part of the data system. For example, errors in water quality may be less acceptable than errors in traffic counts, as the implications are much greater. New approaches likely are needed to conduct continuous quality assurance of data; approaches using machine learning show great promise. Ultimately, there is a need to understand the relations between data error and decision-making, both by individuals and urban-system managers.
Session 2. Analysis and Modeling for Management and Operations Control
This session was dedicated to discussions of analytical capabilities across urban infrastructure in prevention of system failures. Overall, the participants agreed that the analytics is intertwined with data, tools and operations. Urban infrastructure is a complex system, and we need data to understand its workings. One example is the system developed by the Greater Cincinnati Municipal Sewer District, where over 600 sensors are placed throughout the Cincinnati/Hamilton county sewershed. A control system is in place to manipulate the valves and pumps throughout the system based on observational data. The control system is most effective in reducing the overflow of sewage from the combined stormwater-sewer system into waterways.
Coupled with the sewer system is the Cincinnati flood control system that is placed to prevent the Ohio River from flooding inland. Installing sensors and creating a data collection effort at large scale is expensive. There is room for innovation in terms of optimizing the placement of such sensors and creating partnerships to reduce cost.
In power systems, monitoring, modeling, simulation, optimization and control are connected. As the grid grows, the interactions and dependencies also grow.
Hurricanes and cyber attacks are the largest threat. For example, hurricanes not only cause temporary power outages, but also affect the generation and distribution of power. There is a need to develop out-of-the-box solutions to increase the grid resilience. For example, parked electric vehicles could be used as batteries to power buildings during power outages. Out-of-the-box solutions can also include the best use of available sensors. For example, smart meters in buildings allow 2-way communication so this can be used to manage both the supply and demand side of the equation for energy systems.
All the sensors are generating a lot of data and there is a need to use these data to analyze and manage the urban infrastructure. Data can give us information about the past and present, but we will need simulation models to understand the future. Considering that the data, especially observations, come from many different resources and sensors, one can think of a system such as the group on earth observations (GEOSS) platform, HELICS and VOLTRON. GEOSS connects users to multiple heterogeneous databases and provides user-friendly information for decision makers. HELICS is a flexible and scalable open-source co-simulation framework that is used for simulating power systems. VOLTRON is an open-source software platform for connecting data and devices to make decisions based on user needs and preferences.
During the discussion, several issues and opportunities were identified in terms of data analytics, modeling capabilities and infrastructure needs. Many times, data are available in aggregated form so it is difficult to use them. Some datasets such as from utilities have privacy issues. Similarly, data from one domain are not easily available to experts in other domains. There may be an opportunity to create a catalog of all available data including the granularity of the data, their sources and ways to access them. Accomplishing this may require standard protocols for data collection, storage and dissemination. This will also require a better understanding of the intertwined nature of a complex urban system so data from one system can be useful in another.
In terms modeling capabilities, we need to think whether we need a loosely or tightly coupled system, and its pros and cons. There are also many technical considerations including the time and spatial scale, propagation of failure and uncertainties in data and modeling tools.
Access to data and modeling capabilities also need to incorporate the social dimension. For example, how do these impact low-income individuals? Overall, urban infrastructure including utilities and smart systems are generating unprecedented amounts of data. There is a need to develop tools and capabilities to use these data for proper operation and management of urban systems. It is both an optimization problem (how much to collect data from where?), and a computational problem (how to fast process these data to help make decisions?).
Session 3. Synthesis Towards Complexity
The presentations in this session focused on the control and management of inter-connected urban infrastructure, as well as lessons learned from natural disasters in terms of both modeling and planning. The presentation by Michael Saffran from the US Army Corps of Engineers highlighted the extensive risk assessment exercise after Hurricane Katrina, including the assessment of the hazard, the infrastructure impacted by it, and the consequences. It found inconsistent and incomplete levels of protection, old infrastructure components, and redundancy. Repairs were slow.
In the case of City of Cincinnati, Oliver Kroner presented the City’s newly developed sustainability goals and unintended consequences. Among the goals that Cincinnati has been recently pursuing are to decarbonize the energy supplies and to increase energy efficiency. Currently, “green” energy is delivered to 80,000 homes and businesses in Cincinnati. The development of supporting infrastructure (e.g., roads and buildings), however, can also increase flooding due to an increase in impervious surfaces. In the last year Cincinnati experienced three 100-year storms, which resulted in flash flooding and increased landslides. The case of Cincinnati presented a classic example of the complexity of urban multiplex and critical need of sub-system coordination and planning.
Then Steven Bourne from a consulting business, Atkins, shared his experience in city-scale simulations that allow for testing a spectrum of resilience adaption strategies. These simulations hold much promise for characterizing interacting systems within cities such as the economy, people, infrastructure and natural environment.
The presentations in this session sparked lots of discussions from the workshop participants. Group discussions highlighted the challenges through the processes of proactive planning for resiliency and post-event assessment. Gaps and recommendations were identified in terms of both modeling and communications.
In order to simulate the urban multiplex in a dynamic environment, some fundamental knowledge gaps need to be addressed first. For example, given the heterogeneities among cities and various levels of institutions/subsystems, better definitions of urban systems need to be developed. Model developers and users need to set proper expectations on the model adoption; i.e., models that are solution-oriented versus those that help researchers better understand and research the system. Planning and policymaking necessitate not only the understanding of individual systems, but also the knowledge of system-level thresholds or inter-system interactions. In addition, models should be able to adapt to and accommodate unknown unknowns. In other words, models need to have the capacity to quantify uncertainties so as to support dynamic learning and adaption.
Human dimension, as a particularly significant component of urban models, was highlighted in group discussions. Humans and institutions are most important in modeling, but present with the least amount of data and are the hardest to model. In particular, it is challenging to incorporate political processes and governance structure (e.g., central vs. distributed) for a realistic institutional representation in coupled human-natural modeling analyses. Data are critically needed to help us better understand social attitudes (resistance and acceptance to some urban developments) and connections among economic, political, and economic systems. Verification and validation of the role of humans (i.e., multiple stakeholders and communities) and the government sector in the modeling process are needed. Unique challenges in medium and small cities should be built into future decision-making, especially considering the impacts of poverty on infrastructure development, resource allocation, and social equity.
Besides the computing techniques, effective communications were determined to be the key to advance the value of models. It is particularly important to enhance communication between researchers and stakeholders. Practitioners and stakeholders should be involved early in the proposal development process, as well as throughout project planning and execution. More effective strategies are needed to promote inter-agency communications and stakeholder engagement; there is a high value of collecting and analyzing feedback from various sectors and stakeholders.
In consideration of social disparities and environmental injustice, multiple methods of communications should be adopted to reach socioeconomically disadvantaged communities. Besides models per se, there is a need for better understanding of social resistance and acceptance of new models, new concepts, and new policies. The technology advancement and big data movement have greatly facilitated the researchers’ capability to characterize human behaviors, improve the understanding of social networks, and model complex urban infrastructure systems. Model interpretation and knowledge transfer to both researchers and the general public should be carefully integrated. Communications discussed above can be improved by using emerging social media (e.g., crowdsources), as well as sensing technologies.
Modeling and analyzing complex urban systems for effective decisions will need to develop system-level metrics that reflect environmental and socio-economic changes, predict and monitor emerging changes at the system level for early warning, identify feedback mechanisms (both institution and technology), and use science-based short- and long-term forecasts for effective system operations and planning.
Finally, engineers, social and physical scientists, and policy makers tend to address complex urban systems from different angles and usually end up with piecemeal solutions, which lead to inefficiencies in sustainable urban system development. Most professionals are educated in a single discipline and lack the knowledge and skills for communicating across disciplines and for generating broad impacts across sub-systems of a city. Thus education based on interdisciplinary research innovations is needed for the next generation of professionals.
Session 4. Recommendations for Future Research Networks
The first round of discussion focused on general questions of sustainability, and participants talked about how they define urban sustainability from their professional point of view. The agreement was that a sustainable city is one that can support happy life from generation to generation within and beyond its boundaries. It requires resources to be available to all residents. A well-funded government, strong banking, green spaces, arts, public health, security and education are all needed for a city to be sustainable. Livability and happiness indices can help capture these aspects of urban life. And while GDP is often used as a measure of prosperity and happiness of a group, there is not a way to get the other pieces of the puzzle like safety or lower income individual help.
Related to these indices are measures of sustainability that should consider various aspects of the Urban Multiplex. Weak sustainability is economically driven, and balances our current objectives. It is a temporary balance of a few things. We are seeing cities outpacing their locally available resources - an example of people who have temporarily set it up to be successful, but in the long term it is not sustainable - they are vulnerable that the remote resources may no longer be available. On the other hand, strong sustainability will also include environmental and social objectives, as well as sustainability of a larger region that supports city life, making it long-term. Furthermore, at the core meaning of the word sustain is the notion of temporal perspective and change with time. Therefore, static snapshots are only of limited value, and any measure should be dynamic in nature.
This brings us to the question of data. Quantitative sustainability analysis requires measurements, and that requires ubiquitous sensing. While many cities have embraced sensor networks, we still do not have sufficient data. Sensors themselves could be improved. Even when data exist, there are many associated challenges, sharing being one of the toughest. For example, utilities collect lots of data, but many are private and are not shared. These issues are solved on a case-by-case basis, and currently there is no common framework for data sharing and exchange. Institutional support is lacking, as well as political will for this kind of activities. As a consequence, technological solutions will not be embraced for as long as there is no political support.
Oftentimes technologies are developed by academic researchers, but to be effective - as needed in the case of sustainable urban systems - they have to be adopted by cities. It is advisable to engage with cities early and co-develop technological solutions, or to modify existing technologies to suit city needs.
Technologies that use streaming data are preferable for flexibility and on-the-fly control of urban infrastructure. Power grid planning is a good example of the critical need of connecting quantitative analysis with rigorous data monitoring and collection. Another example is the sensing and control system developed by the Greater Cincinnati Municipal Sewer District.
The objective of the second round of discussion was to outline recommendations for future research based on needs and gaps identified over the previous two days of presentations and deliberations.
All participants agreed that urban infrastructure should be treated as a complex system of systems in the nexus of energy, water, transportation, communication, and food. Adoption of this philosophy by the community is a critical part of affecting change - communities must be excited about studies like this, otherwise the results will never be adopted. Engagement starts with the city government (the planning commission in particular), because ultimately they will be the ones using the products that the scientific community will deliver.
From technological and scientific viewpoint, there is a need to address problems on different time scales, from real-time to long term planning. Detailed city simulations to explore a variety of resilience adoption strategies could be very helpful in addressing the problem of scales.
Participants also discussed the need to better understand the human and institutional dimensions in urban areas - including feedbacks among different levels of government (e.g., city, county, state) and different sectors (e.g., power, water, social institutions). How will any recommended management strategies for the Urban Multiplex impact communities? Will these solutions help impoverished groups? What are the forecasts for future demographic shifts under climate change? How will they change the carbon budgets of a city - note that many cities do not have a well-understood carbon budget, or it is not detailed enough to be actionable. Will recommended solutions help create new jobs and opportunities, or lead to new problems? How will they impact public health? What are the current weak links in the urban multiplex and how does this differ among cities?
As these questions are pondered, we should pay close attention to potential disparity in how technological solutions will impact different communities. Many cities have pockets of concentrated poverty, with as high as 40% of population below poverty level. These neighborhoods have high mortality and unemployment rates, water, environmental and transportation issues. They tend to be in heat islands within cities themselves. So, how do we revitalize these areas in the long-term? Will these solutions change utility costs? In what way? In communities where utility costs are 30% of income, and people are $125 away from homelessness, will these technologies tip them in the positive direction or force them out of their homes? Answers to these questions require high-resolution data, which are not easy to find.
Green technologies have been used in cities for some time now, but we do not fully understand their impact, and more studies are needed to evaluate it across communities. Are there potential scenarios where installation of green infrastructure would benefit one community and hurt another? How do we use this information to form policy?
No matter what challenge we set to analyze, we will quickly come to a realization that we cannot solve them one at a time. They are all interconnected, and a multi- and interdisciplinary approach is needed. Taking a systems approach to understanding how cities function - from infrastructure to communities and human behavior - is the only hope of producing technological solutions that will contribute to strong sustainability.
- Lilit Yeghiazarian - Chair (University of Cincinnati)
- Ning Ai (University of Illinois-Chicago)
- Sankar Arumugam (North Carolina State University)
- Jerad Bales (CUAHSI)
- Ximing Cai (University of Illinois-Urbana Champaign)
- Heather Golden (USEPA)
- Venkatesh Merwade (Purdue University)
- Claire Welty (University of Maryland, Baltimore County)
- Stephen Bourne, Atkins
- Jeff Horsburgh, Utah State University
- Zhenyu (Henry) Huang, Pacific Northwest National Laboratory
- Reese Johnson, Metropolitan Sewer District of Greater Cincinnati
- Camille Jones, City of Cincinnati Health Department
- Oliver Kroner, City of Cincinnati Office of Environment & Sustainability
- Lewis Lehe, University of Illinois - Urbana Champaign
- Jeff Oxenham, Cincinnati Stormwater Management Utility
- Anu Ramaswami, Princeton University
- Michael Saffran, U.S. Army Corps of Engineers
All Participants (alphabetically)
- Ai, Ning University of Illinois - Chicago
- Arumugam, Sankar North Carolina State University
- Bales, Jerad Consortium of Universities for Advancement of Hydrologic Science, Inc
- Bourne, Stephen Atkins
- Cai, Ximing University of Illinois - Urbana Champaign
- Dinkins, Sam Ohio River Sanitation Commission
- Golden, Heather US Environmental Protection Agency
- Habib, Ayman Purdue University
- Hamilton, Bruce National Science Foundation
- Harris, Angela North Carolina State University
- Horsburgh, Jeff Utah State university
- Huang, Zhenyu (Henry) Pacific Northwest National Laboratory
- Humphreys, Jeffrey Duke Energy
- Johnson, Reese Metropolitan Sewer District of Greater Cincinnati
- Jones, Camille Cincinnati Health Department
- Kern, Jordan North Carolina State University
- Kroner, Oliver City of Cincinnati Office of Environment & Sustainability
- Lehe, Lewis University of Illinois - Urbana Champaign
- McDonald, Douglas US Department of Transportation
- Meidani, Hadi University of Illinois - Urbana Champaign
- Merwade, Venkatesh Purdue University
- Oxenham, Jeff Cincinnati Stormwater Management Utility
- Paisley, Benjamin University of Cincinnati
- Ramaswami, Anu Princeton University
- Ranjithan, Ranji North Carolina State University
- Riasi, Sadegh University of Cincinnati
- Saffran, Michael US Army Corps of Engineers
- Stone, Harry Ohio River Basin Alliance
- Straus, Katie University of Cincinnati
- Tartakovsky, Alexandre Pacific Northwest National Laboratory
- Ukkusuri, Satish Purdue University
- Welty, Claire University of Maryland, Baltimore County
- Yeghiazarian, Lilit University of Cincinnati
- Yu, David Purdue University