As storm events in cities are becoming more regular and more intense, urban watersheds and their stormwater networks are becoming stressed beyond their design capacities leading to more frequent and destructive urban flooding events. These system failures are only exacerbated due to infrastructure that is aging, landuse that is continuously changing in response to demographic shifts, and system complexity that only continues to increase. But traditional engineering interventions meant to improve upon these systems are unfavorable as they entail large-scale and cost-prohibitive infrastructure construction, and only provide a static solution to a dynamic and evolving problem. Additionally, these traditional forms of engineering interventions often center on physical solutions for systems that are often layered with social, political, and operational complexities.
My research focuses on building intelligent and resilient urban watersheds using a multi- disciplinary approach that (i) employs sensor and data acquisition technologies for improved and adaptive system-level performance, and (ii) utilizes systems science to integrate socio-political complexity into modeling and analysis of interdependent infrastructure systems. Below, I provide detail for both of these points, and the research questions being asked at varying scales of the watershed systems. Further, I discuss the need for engineering research to be grounded in collaboration across all academic disciplines, and alongside private, public, and community stakeholders.
The recent accessibility of low-cost sensors, microcontrollers, and wireless communication technology has made it possible for the existing stormwater networks to be retrofitted with an assortment of cyber-physical technologies that allow for inexpensive, versatile, minimally-invasive, and fully- automated stormwater control interventions (e.g. hydraulic valve operated by cellularly-connected actuator). With the demonstrated success of automating individual components of a stormwater network (i.e. the micro-scale), there now exists the possibility for these individual components to be strategically coordinated and operated to achieve system-level and multi-objective automated control, potentially leading to dramatic changes in how entire urban watersheds are able to dynamically respond to storm events.
Additionally, while initial focus of intelligent water infrastructure was on volumetric control (e.g. combined-sewer overflow reduction), imperative to the functioning and health of an urban watershed is its underlying water quality, with nonpoint source pollution (e.g. urban stormwater runoff) recognized as one of our greatest environmental threats. However, real-time sensing and control of water quality is a far more difficult undertaking due to (a) the lack of sensors able to immediately measure the most critical water quality parameters (e.g. fecal indicator bacteria) and (b) the computational complexity to successfully model nonpoint source pollution dynamics.
Finally, as intelligent water technologies become more ubiquitous in water resources engineering interventions, there exists a need to better understand what is the future demand of emerging information and communication technologies for employment/deployment, and whether our manufacturing infrastructure will be able to meet this future demand.
For the emergent and disruptive technologies from above to be positively exploited, there exists a need to understand societal interaction with and adoption of them. Furthermore, to ensure any of the new technologies used and new knowledge generated benefit the populations and communities they were designed for, there must (a) be an understanding of how these technologies may transform the very socio-political fabric underlying their adoption, and (b) how the essential information about these technologies disseminate such that they can reach the communities most in need of having access to it.
Furthermore, major environmental threats have demonstrated the dependencies and interdependencies of infrastructure systems. For example, during extreme environmental events, the failure of an urban area’s power network could cause cascading failures in other infrastructure lifelines (e.g. water distribution networks). The recent development of complex computational tools and modeling techniques has allowed for a “network of networks” approach to modeling said interdependent infrastructures, thus, allowing for analyses of lifeline infrastructures interdependencies and their resilience to widespread, cascading failures. Additionally, such a “network of networks” approach to infrastructure modeling has given rise to new tools for integrated water management efforts. For example, such modeling may allow initiatives such as the “One Water Movement” to analyze current and potential future connections between urban water distribution and stormwater networks where non-potable water reuse is feasible.
Finally, large-scale computational tools have allowed for climate projections to be downscaled to the neighborhood scale. Thus, future weather events based on global climate change models can be predicted and used to test the future resilience and agility of infrastructure interventions being considered in the present-day.
How can we use real-time data monitoring of surrogate water quality parameters to develop real-time predictive modeling capabilities for critical water quality parameters unable to be measured in real-time?
How can we utilize bottom-up computational modeling approaches – such as agent-based modeling – to simulate the interaction of our water infrastructure with the communities they serve to better improve said infrastructure’s design, operation, and information dissemination?
How can we develop system-scale real-time control of urban stormwater systems to meet the needs and competing desires across a variety of stakeholders?
What is the impact of predicted future weather events on these dynamic and redesigned intelligent infrastructure?
What are the priority components of water and stormwater infrastructures to make said infrastructure more resilient to widespread, cascading failures that can be triggered by natural or manmade disruptive events? Additionally, what components allow for new and/or improved integrated water management efforts and infrastructure intervention?
How can we characterize the future technological demand for intelligent urban water infrastructure? What does the future projection of emerging technologies, data requirements, energy impacts, and interconnectivity with industrial sector systems look like for water and wastewater?
I believe research that is shaped through relationship building and collaboration with local governmental and non-governmental entities (e.g. USGS, water utilities, Anthropocene Alliance) is what allows for the development of real and feasible engineering research solutions that are grounded in local needs of the communities they are meant to serve. Additionally, these partnerships allow for said communities and organizational entities a means to utilize the scientific and technological capabilities of the Department of Energy National Laboratories built to serve the public good.
Sara P. Rimer
Argonne National Laboratory
This event is supported by the National Science Foundation, Award #1929601. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.