Modeling Resilience for Sustainable Food, Energy, and Water Systems

Efficient and sustainable agricultural systems are complex and interdependent. In the past, agriculture was dependent on water resources, fertilized soil, and weather, contemporary agriculture is now heavily dependent on electricity, transportation, and other emerging technologies such as the Internet of Things (IoT). When systems are connected, complexity in structural topology and interdependency among them increases. Complexity affects system functions. Furthermore, when the type of connections and entities in a complex system increases the analysis of such systems becomes more challenging. Previous studies have demonstrated the ways that a local failure in an interdependent system can propagate from one system to another escalating failures. In addition, many systems are designed locally. When such systems are aggregated, they tend to encounter unanticipated demands and transformation of services in order to adapt to novel from the overall system. These changes can also leading to reduced robustness and resilience. Therefore, it is generally unwise to analyze the system resilience of aggregated systems in terms of its separate components. FEWtures is a multidisciplinary project considering different technologies to improve profitability and resilience in agricultural system. FEWtures consists of economic analysis, global-scale impact, engagement and policy, business development, resilience and metrics, agriculture, ammonia, energy, water supply and treatment, communication and information technology, and education. In this paper, we define a multilayer model to study resilience in FEWtures. We use our proposed multilayer framework to model FEWtures. We can recognize multiple loops in the abstract model. These loops shows that how different entities in various layers are dependent to each other and how one failure in one layer can affect the operation of the other layer. The dependency edges in the model have influences on system resilience while the topology of a network in each layer affect on resilience in each layer. We will calculate the amount of dependency through the risk analysis, and measure the vulnerability of the system due to the disruption of each connection.