Using Fuzzy Cognitive Maps to Engage Stakeholders in the Search for Solutions to Emerging Environmental Challenges
dc.contributor.author | Roston, Benjamin Harris | en |
dc.contributor.committeechair | Rippy, Megan A. | en |
dc.contributor.committeemember | Schenk, Todd Edward William | en |
dc.contributor.committeemember | Grant, Stanley | en |
dc.contributor.committeemember | Misra, Shalini | en |
dc.contributor.department | Civil and Environmental Engineering | en |
dc.date.accessioned | 2025-06-10T08:02:10Z | en |
dc.date.available | 2025-06-10T08:02:10Z | en |
dc.date.issued | 2025-06-09 | en |
dc.description.abstract | Inland freshwater salinization is an emerging environmental problem that threatens freshwater ecosystem health, agricultural productivity, and the sustainability, reliability, and safety of drinking water supplies around the world. This body of work focuses on the Occoquan Reservoir in Northern Virginia and uses fuzzy cognitive maps (FCMs) to characterize stakeholder understanding of the social-ecological system (SES) for freshwater salinization in the Occoquan. A total of thirty-five stakeholders from in and around the Occoquan system participated in this work by constructing personalized mental models for salinization in the region. These FCMs were evaluated with respect to (1) their ability to reveal barriers and opportunities for stakeholder-driven, bottom-up management of the FSS, (2) their ability to capture physically meaningful information about the SES when aggregated to represent collective perspectives, and (3) their dynamics - e.g., are feedback loops between environmental outcomes and management actions present in stakeholder FCMs and, if so, what might they imply for managing the SES? My results suggest that FCMs can reveal barriers and opportunities for collective salt management, with preferred modes of governance and uncertainty about the sewershed constituting barriers, and the watershed (specifically winter anti-icing and deicing activities) representing an area of agreement where collective action is more likely. FCMs were found to capture meaningful biophysical information about the system (e.g., reproducing the balance between watershed and sewershed salt sources). Because different FCMs captured different, but equally valid, salt source ratios, their comparison provides an opportunity for perspective taking and learning. My results indicate that dynamic motifs like feedback loops are relatively rare in individual FCMs, but emerge when multiple perspectives are aggregated. This suggests that stakeholders collectively (if not individually) perceive a dynamic and interconnected SES for freshwater salinization in the Occoquan. However, gaps in systems understanding remain that could constitute barriers to effective management - for instance, the absence of decision rules for managing salts in stormwater, one of the three principal water streams that contribute salts to the Occoquan system. In addition, not all stakeholders felt that the feedback loops articulated by others (or collectively) made sense for the system. While this may in part be due to the introduction of noise during aggregation, cognitive bias and the presence of relationships that were simply viewed differently also played a role. Recognizing these diverse "truths" is likely to be important for collective decision making and collaborative governance of freshwater salinization in the region. In performing the analyses required for this work, it became obvious to me that the accessibility of advanced simulation tools for working with FCMs is somewhat limited. To address this, I developed the R package fcmconfr, which provides tools for FCM aggregation and dynamic simulation, along with features for incorporating uncertainty in individual FCMs and propagating that uncertainty through to the aggregate. It is my hope that this contribution will make FCM analysis more straightforward and enable researchers and practitioners from a variety of backgrounds to use FCMs in support of stakeholder and community-engaged research. | en |
dc.description.abstractgeneral | Inland freshwater salinization (when salt levels build up in rivers, lakes, and reservoirs) is an emerging environmental problem. It can harm ecosystems and make drinking water less safe and reliable. This project focuses on the Occoquan Reservoir in Northern Virginia and explores how local stakeholders (people like water managers and government officials) understand and manage this challenge. I worked with thirty-five stakeholders to create "mental models" of freshwater salinization. These models included salt sources, management opportunities, and social and environmental impacts. The models, called fuzzy cognitive maps (FCMs), show important parts of the system and how they connect. I used them to explore three main questions (1) What are the barriers and opportunities for local, stakeholder-driven salt management? (2) Can FCMs capture meaningful information about how the environment really works? and (3) Do FCMs contain important patterns, like feedback loops between actions and outcomes, that might help us manage salt better? The results show that FCMs are a powerful tool. They helped identify both barriers and opportunities for managing salt. For example, while there was uncertainty about salt added by the sewer system, stakeholders agreed that managing road salt could help reduce salt pollution. FCMs also captured physical patterns, like the balance between salt added by the sewer and salt added by the watershed. Feedback loops, where actions and outcomes reinforce or balance each other, were rare in individual FCMs. However, they became clearer when multiple perspectives were combined. This suggests that while no one person saw the whole system, the group perceived a more dynamic and interconnected version of it. Gaps in understanding were observed, however, and these could be barriers to effective decision-making. For example, no feedback loops linked stormwater, wastewater, and drinking water systems, even though all three are important for salt management in the Occoquan. While working on this project, I noticed that tools for building and analyzing FCMs can be hard for non-experts to use. To address this, I created a new R package called fcmconfr. fcmconfr makes it easier to combine different perspectives, simulate system behavior, and handle uncertainty. I hope this tool will make it easier to use FCMs to understand emerging environmental problems like freshwater salinization. | en |
dc.description.degree | Doctor of Philosophy | en |
dc.format.medium | ETD | en |
dc.identifier.other | vt_gsexam:43853 | en |
dc.identifier.uri | https://hdl.handle.net/10919/135435 | en |
dc.language.iso | en | en |
dc.publisher | Virginia Tech | en |
dc.rights | In Copyright | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
dc.subject | Freshwater salinization | en |
dc.subject | Fuzzy Cognitive Maps (FCMs) | en |
dc.subject | social-ecological systems (SES) | en |
dc.title | Using Fuzzy Cognitive Maps to Engage Stakeholders in the Search for Solutions to Emerging Environmental Challenges | en |
dc.type | Dissertation | en |
thesis.degree.discipline | Civil Engineering | en |
thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
thesis.degree.level | doctoral | en |
thesis.degree.name | Doctor of Philosophy | en |
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