ITR/AP+IM: Information Processing for Integrated Observation and Simulation BAsed Risk Management of Geophysical Mass Flows

实时环境观测和预报系统（EOFS）将彻底改变科学家分享环境信息的方式，并为打破科学家与社会之间的传统信息壁垒提供了机会。EOFS已经在使用中，但它们往往是小规模的、特定于应用程序和领域的独立系统。有必要向多用途共享系统发展，以便灵活地适应信息消费者不断变化的需求。 所需要的是大规模的、共享的、异构的分布式系统，其广泛使用各种基于传感器的输入、复杂的数值模拟、移动的和嵌入式实时系统组件、无线和有线通信、高性能计算机和高容量存储系统。 这个ITR中型项目已经组建了一个跨学科的团队，包括计算机科学和环境科学研究人员，除了试点用户的异质基础。 该小组将合作开发软件技术，使EOFS能够有效地发展，并在正确的时间以正确的形式向正确的用户提供有关环境的量化可靠信息。该项目的重点是河口和沿海地区的EOFS。选择这些地区是因为它们是高度可变的自然系统，受到强烈的人类活动的影响，并具有巨大的社会，环境，经济和文化价值。为EOFS开发缺失的集成概念和技术，重点是质量可扩展的信息处理，存储和访问（计算机科学研究）。闭合环境模型和传感器之间的回路，并在现有原型的基础上为具有多种且往往相互冲突的用途的河口实施下一代EOFS（环境观测和预报系统研究）;iii.使用、评估和改进EOFS原型，以促进科学发现、自然资源管理和应急反应，从而将健全的科学纳入具有关键区域重要性和国家重要性的业务和管理决策（环境科学和管理应用）;制定多层次、跨学科的试点教育方案，在环境信息技术的概念化、开发和使用方面对青年、计算机科学家、环境科学家和从业人员进行交叉培训（教育影响）。

Real-time Environmental Observation and Forecasting Systems (EOFS) will revolutionize the way scientists share information about the environment and represent an opportunity to break traditional information barriers separating scientists from society at large. EOFS are already in use, but they tend to be small-scale, application- and domain- specific, stand-alone systems. There is a need for evolution towards multi-purpose shared systems designed to adapt flexibly to evolving needs of information consumers. What is required are large-scale, shared, heterogeneous distributed systems that make extensive use of diverse sensor-based inputs, sophisticated numerical simulations, mobile and embedded real-time system components, wireless and wired communications, high-performance computers, and high capacity storage systems. This ITR medium project has assembled an inter-disciplinary team, including computer science and environmental science researchers in addition to a heterogeneous base of pilot users. This group will collaborate to develop software technology which will enable EOFS to evolve efficiently, and to deliver quantifiably reliable information about the environment at the right time and in the right form to the right users. The project focus is on EOFS for estuarine and coastal regions. These regions are selected because they are highly variable natural systems subject to intense human activity and with great social, environmental, economic and cultural value.The research will include:i. Developing missing integration concepts and technologies for EOFS, with emphasis on quality-scalable information processing, storage and access (the computer science research).ii. Closing the loop between environmental models and sensors, and implementing a next generation EOFS based on an existing prototype for an estuary with multiple and often conflicting uses (the environmental observation and forecasting systems research);iii. Using, evaluating and refining the EOFS prototype for scientific discovery, natural resources stewardship and emergency response, thus incorporating sound science in operational and management decisions of critical regional importance and national significance (the environmental science and management applications);iv. Developing pilot multi-level, inter-disciplinary educational programs that cross-train young people, computer scientists, environmental scientists and practitioners in the conceptualization, development and use of environmental information technology (the education impact).