Approaches for performing flood hazards modeling and risk assessment at federal, state, and local agencies are undergoing emergent challenge for consistent metadata and cataloging systems to ensure the sharing of flood risk data in a Findable, Accessible, Interoperable, and Reusable (FAIR) manner. This paper explores the suitability of a suite of software and specifications developed by the Earth observation community for environmental modeling, which adhere to the FAIR principles not only for managing published or authoritative data but throughout the model development and flood hazard analysis phases. Specifically, we evaluate the SpatioTemporal Asset Catalog (STAC) in a pilot study undertaken as part of the Future of Flood Risk Data (FFRD) initiative of FEMA. The experimental results indicate the STAC ecosystem offers a flexible cloud native approach for linking data, managing metadata, and cataloging collections of models. Further, the STAC framework shows favorable results in a probabilistic and other use cases.

中文翻译：

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评估 SpatioTemporal Asset Catalog，用于管理和发现 FAIR 洪水灾害模型


在联邦、州和地方机构执行洪水灾害建模和风险评估的方法正面临对一致的元数据和编目系统的紧急挑战，以确保以可查找、可访问、可互操作和可重用 （FAIR） 的方式共享洪水风险数据。本文探讨了地球观测社区开发的一套软件和规范对环境建模的适用性，这些软件和规范不仅在管理已发布或权威数据方面遵守 FAIR 原则，而且在整个模型开发和洪水灾害分析阶段都遵守 FAIR 原则。具体来说，我们在一项试点研究中评估了时空资产目录 （STAC），该研究是 FEMA 洪水风险数据的未来 （FFRD） 计划的一部分。实验结果表明，STAC 生态系统提供了一种灵活的云原生方法，用于链接数据、管理元数据和对模型集合进行编目。此外，STAC 框架在概率和其他用例中显示出良好的结果。