Graduation Year


Document Type




Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department


Major Professor

Qiong Zhang, Ph.D.

Committee Member

Maya Trotz, Ph.D.

Committee Member

James R. Mihelcic, Ph.D.

Committee Member

Rebecca Zarger, Ph.D.

Committee Member

Ali Yalcin, Ph.D.


Climate Change, Resource Recovery, Stakeholder Engagement, System Dynamics, Technology Adoption, Wastewater Reuse


Coastal communities and ecosystems around the world are some of those most vulnerable to the impacts of climate change. In particular, the wastewater treatment systems in these areas are on the forefront of the effects of increasing frequency, duration, and intensity associated with extreme weather events. As such, decision making about adopting new wastewater technologies or transitioning to an improved treatment portfolio is an important area of research for coastal communities because they are critically linked to the health of the nearby aquatic ecosystems (i.e. tourism, fishing, cultural heritage, climate protection).

The decision making process about technology adoption and transitions in wastewater treatment, regardless of the technology’s scale— onsite, community, or centralized— requires the navigation of complex interactions between human, engineered, and environmental systems. However, the navigation of this complexity is often siloed, lacks innovation, and is performed using the reductionist approach. Consequently, the work from this study fills the knowledge gap by using systems-based approaches to investigate the factors and relationships that influence technology adoption, sustainability, and transitions to provide decision makers with tools that simulate system-level responses to strategies promoting context-appropriate wastewater systems.

Two case studies and a comparison are presented. The first case study is a bottom-up, grassroots-based perspective in Belize that innovatively employs social science field methods to develop a community-influenced, theory-informed system dynamics (SD) model where marketing, social, and technical strategies are implemented to increase the adoption and sustainability of systems that productively reuse wastewater (i.e. wastewater-based resource recovery (RR) systems). Approaches such as increasing site demonstrations, a marketing strategy, and changing tank configurations, a technical strategy, had significant impacts to the system’s sustainability; only the increase in site demonstrations influenced the adoption performance measure significantly. Furthermore, the unique mixed methods approach brings to light a discrepancy in user behavior (i.e. the actual and reported number of users of the wastewater systems) that impacts the sustainability performance measure. With this insight, the technical strategy (i.e. increase the options for tank configurations) shows the way adaptations to variations in system users improves the RR system’s effluent water quality (i.e. sustainability performance measure). Overall, the system’s sustainability was most dramatically improved when a paradigm shift targeting users’ behaviors was introduced by changing the structure of the SD model. The paradigm shift emphasized training for community members in the importance of accurate RR system design, operation, and maintenance. The results improved their value for recovered resources, desire to avoid future economic and environmental impacts of failed systems, and long-term wastewater management capabilities.

The second case study is in the Florida Keys where a multi-level perspective (MLP) of socio-technical transitions was adapted to the site-specific context to develop the SD model of municipal decision making. This model reflects a top-down (i.e. landscape-level), policy-driven approach that promotes the installation and expansion of centralized and community-based wastewater systems to meet the community’s needs while also improving coastal water quality (i.e. nutrient loading). The model’s parameters were populated with local information from a review of state-level data (e.g. policies, wastewater permit details, and effluent water quality standards), government documents, engineering reports, and public records from Monroe County. The model was then simulated under normal and climate change conditions (i.e. more frequent and longer duration extreme events). The existing decision-making process resulted in a wastewater treatment portfolio that was ineffective at reducing nutrient loading under climate change conditions. As such, climate change (i.e. variable frequency and duration of extreme events) and its impacts (i.e. variable magnitudes of wastewater system failure) were incorporated into the decision making structure, and the wastewater infrastructure portfolio and performance measures (i.e. nutrient loading, reliability) improved. Furthermore, sensitive parameters (i.e. influent nutrient concentration, flow rate, and extreme event frequency) are used as leverage points within the regime-level of the model to develop strategies (i.e. socio-economic decision making, technology and economic policies, and a socio-technical behavior change approaches) that facilitate the transition to an improved wastewater treatment portfolio. The best impacts to the performance measures were the socio-technical strategy (i.e. implementing a niche-level RR system such as a urine diversion technology that reduces the influent wastewater concentration) which influenced the most change to the nutrient loading and the technology and economic policy (i.e. using a land cost factor (LCF) to economically disincentivize centralized investment and changing the community-level treatment to a membrane bioreactor) which improved the reliability performance measure.

Overall, a viable path for holistically improving the decision making process for coastal wastewater treatment portfolios is to pursue an MLP socio-technical transition that combines the aforementioned model structures of top-down (i.e. policies or institutional support from the landscape-level) and bottom-up (i.e. behaviors at the niche-level) efforts to promote suitable environments for context-appropriate wastewater systems (i.e. RR innovations) to move into the wastewater regime. Within the combined model structure, sensitive parameters from the community and national levels (i.e. niche, landscape, respectively) should be used as policy levers to facilitate broader adoption. For instance, community training in the importance of accurate RR system design, operation, and maintenance should be coupled with landscape level resources and initiatives such as a comprehensive wastewater plan (i.e. sets expectations for various scales of wastewater systems and enforces water quality standards) to effectively break open the wastewater regime so that RR systems enter into the mainstream treatment portfolio. Additionally, both study sites revealed the importance of behavior change as necessary and effective in facilitating transformative change to the wastewater systems’ performance measures. As such, to operationalize the combined approach, stakeholders from each level (i.e. niche, regime, and landscape) must engaged in the transition planning process, strategy development, and behavior change.