Graduation Year


Document Type




Degree Name

MS in Environmental Engr. (M.S.E.V.)

Degree Granting Department

Civil and Environmental Engineering

Major Professor

James R. Mihelcic, Ph.D.

Co-Major Professor

Qiong Zhang, Ph.D.

Committee Member

Kebreab Ghebremichael, Ph.D.


community-management, Latin America, SDG 6, sustainability, system dynamics


Globally, the focus of environmental engineers and water, sanitation, and hygiene (WASH) professionals in the rural water sector has shifted from building new technology to ensuring long-term functionality of water systems and closing the access gap between urban and rural residents. In Latin America and the Caribbean, the main challenges to ensuring clean water for all rural residents is poor service delivery quality and limited sustainability over time. A common management strategy in the region, and globally, is community-management, where community members manage, operate, and maintain the water system through cost sharing and financial management. The failure of community-managed water systems (CMWS) to sustain water services over the expected service life has been well-documented. Therefore, the goal of this research is to improve the performance of community-managed water systems, using Bolivia and Colombia as case studies.

CMWS are complex systems composed of technical, social, environmental, managerial, and financial components that evolve over time. However, most approaches to identifying and addressing problems with CMWS in Latin America disregard interactions and feedback among system components, rely on largely anecdotal evidence, and only consider one point in time. Consequently, this study fills those gaps by using a quantitative systems approach to model the performance of CMWS over the system life and recommend strategies to improve performance to the target threshold. The model utilizes monitoring data from the Rural Water and Sanitation Information System (SIASAR, in Spanish) to quantify performance as a function of the state of water system infrastructure, water service level, and state of service provider.

The models of performance for Bolivia and Colombia were developed in the same fashion, using the literature review and SIASAR components to identify important factors, assessing current performance through a historical system state (reference mode) of SIASAR data, and developing a stock-flow diagram to model performance over time and test strategies to improve performance. Both models were good fits for the SIASAR data (Bolivia MSE: 3.5%; Colombia MSE:0.76%) and were driven by largely the same mechanisms: one reinforcing and one balancing loop for influence of economic management and maintenance provision on system, and the linear degradation of the infrastructure and service provider due to aging and disinterest or migration. The sensitive variables identified from the models were monthly tariffs or annual income, maintenance costs, user’s willingness to pay, service provider’s ability to detect problems in system, and legalization of water system.

The sensitive variables and important factors were leveraged into three strategies to improve performance for each country. The best strategy for both countries was to professionalize the service provider, resulting in increased operation cost but improved capacity to detect and address problems. This strategy should be accompanied by a shift in focus from corrective (reactive) to preventive (proactive) maintenance. The other strategies relating to external financial support, legalization, and user’s willingness to pay had varying levels of effectiveness but resulted in similar results to professionalization when combined. Along with the recommended strategies for each study location, the model can be used as a communication and decision-making tool for rural water stakeholders to test interventions and shape future policy and funding mechanisms. The study’s approach demonstrates how system dynamics tools can utilize monitoring data to simulate behavior and test the effectiveness of possible interventions. Additionally, SIASAR’s conceptual model and survey data analysis would benefit from accounting for the interconnections and feedback among system parts. Furthermore, the approach could be implemented in other study locations or to address other context-specific problems in rural water systems, like regional, ethnic, or socio-economic differences.