Artificial Intelligence Methods for Water-Environment-Food-Energy Nexus

With the steady urbanization process, the global population and economy continuously increase, and then the interconnected systems of water, environment, food, and energy have posed unprecedented challenges as well as opportunities. The close relationships of the four sectors increase the in-depth understanding of the need for a nexus perspective. Researches and discussions associated with the issues relating to the water-environment-food-energy nexus can effectively promote the sustainable development of human society and address the increasing worldwide problems, like flood disasters, energy crises, food shortages and environmental pollution. However, due to the growing extreme climate events and human activities, it becomes more and more difficult to identify the complex relationship in the system of systems. The booming development of advanced artificial intelligence approaches can provide new possibilities to handle many practical engineering problems. Using well-designed mathematical models and a mass of desired datasets, artificial intelligence methods usually possess the advantages of high response speed, strong generalization ability and high data-processing capacity. Under this background, the employment of advanced artificial intelligence approaches is helpful to promote the applied sciences involved in the linkages between water, environment, food, and energy systems and then contribute to the implementation of sound policies and sustainable solutions under the rapidly changing environments.
This Research Topic aims to provide an opportunity for scholars to share their latest research findings related to advanced artificial intelligence approaches for the water-environment-food-energy nexus. In this Research Topic, high-quality research papers in the following themes are invited (not an exhaustive list):
• Growing trends in water-environment-food-energy nexus
• Concept and framework of water-environment-food-energy nexus
• Governance strategies in water-environment-food-energy nexus
• Artificial intelligence methods for water-environment-food-energy nexus
• Machine learning approaches for water-environment-food-energy nexus
• Cloud computing and big data for water-environment-food-energy nexus
• Multi-objective optimization for water-environment-food-energy nexus
• Risk quantification and management for water-environment-food-energy nexus
• Innovative technologies and policies for water-environment-food-energy nexus
• Future energy and environmental technologies obeying water and food constraints