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This paper summarizes the findings of an extensive review of literature that was conducted to understand the historical state of the food, energy, and water nexus in the Lake Atitlan basin and to recommend incentive-based, long-term sustainable policies to become a significant driver to Guatemala’s tourism industry and GDP growth. The SWAT (Soil and Water Assessment Tool) was implemented in the basin to work towards the goal of simulating nutrient loading. A key conclusion of this review study is for the local population to have advocacy for the “zero wastewater discharge to Lake Atitlan” initiative to bring long-term benefits to lake water quality. One of the recommended policy decisions is to seek external financing from international agencies like the World Bank at low-cost interest (IDA Loans) to implement waste management systems and pay this external debt by putting a small but affordable tax on tourists visiting the lake. Once a culture of zero municipal effluent discharge to Lake Atitlan is adopted by the local population, the livelihood of residents will become sustainable and the standard of living will increase because of improved water and air quality, making Lake Atitlan a haven of tourism for Guatemala and lifting its economy.

Sustainable provision of food, energy and clean water requires understanding of the interdependencies among systems as well as the motivations and incentives of farmers and rural policy makers. Agriculture lies at the heart of interactions among food, energy and water systems. It is an increasingly energy intensive enterprise, but is also a growing source of energy. Agriculture places large demands on water supplies while poor practices can degrade water quality. Each of these interactions creates opportunities for modeling driven by sensor-based and qualitative data collection to improve the effectiveness of system operation and control in the short term as well as investments and planning for the long term. The large volume and complexity of the data collected creates challenges for decision support and stakeholder communication. The DataFEWSion National Research Traineeship program aims to build a community of researchers that explores, develops and implements effective data-driven decision-making to efficiently produce food, transform primary energy sources into energy carriers, and enhance water quality. The initial cohort includes PhD students in agricultural and biosystems, chemical, and industrial engineering as well as statistics and crop production and physiology. The project aims to prepare trainees for multiple career paths such as research scientist, bioeconomy entrepreneur,more »agribusiness leader, policy maker, agriculture analytics specialist, and professor. The traineeship has four key components. First, trainees will complete a new graduate certificate to build competencies in fundamental understanding of interactions among food production, water quality and bioenergy; data acquisition, visualization, and analytics; complex systems modeling for decision support; and the economics, policy and sociology of the FEW nexus. Second, they will conduct interdisciplinary research on (a) technologies and practices to increase agriculture’s contributions to energy supply while reducing its negative impacts on water quality and human health; (b) data science to increase crop productivity within the constraints of sustainable intensification; or (c) decision sciences to manage tradeoffs and promote best practices among diverse stakeholders. Third, they will participate in a new graduate learning community to consist of a two-year series of workshops that focus in alternate years on the context of the Midwest agricultural FEW nexus and professional development; and fourth, they will have small-group experiences to promote collaboration and peer review. Each trainee will create and curate a portfolio that combines artifacts from coursework and research with reflections on the broader impacts of their work. Trainee recruitment emphasizes women and underrepresented groups.« less