资源环境科技发展态势分析平台

This paper introduces the concept of the HydroGrid as a framework to describe connected water systems. We draw upon the knowledge and engineering experience employed in electrical grid operations to outline mirroring concepts in the HydroGrid, with a particular focus on monitoring, analysis, and control. The electrical grid is well monitored in real time. Monitoring data are used for dynamic analysis, and based on analytical projections, the grid is controlled to reduce the chance of cascading failures. We discuss analogous developments for the HydroGrid, using the example of microbial surface water contamination for illustration. Emerging technologies in advanced materials, signal transduction and wireless communications enable development of autonomous mobile devices for dynamic microbial water quality monitoring. As this technology matures, the devices will have the capability to stream real-time or near-real-time data for analysis with stochastic models of contaminant fate and transport. Modeling results, combined with controllability analysis of water systems, can then be used to determine system-wide prevention and mitigation strategies. Progress is measured with probability-based metrics of HydroGrid sustainability such as reliability, vulnerability, and resilience. We highlight challenges in data requirements and processing, and finally, we broadly discuss interdependent functions of the HydroGrid such as human and animal health services, food safety, and aquatic ecosystems health.

Plain Language Summary This paper introduces the HydroGrid as an interconnected system of water. Through analogies with the electrical grid, we describe emerging technologies in monitoring, analysis, and control of the HydroGrid. We broadly discuss interdependent functions of the HydroGrid such as human and animal health services, food safety, and aquatic ecosystems health. The state of the HydroGrid is assessed using sustainability measures such as reliability, vulnerability, and resilience that originated in engineering reliability theory.