Flood Markup Language – A Standards-based Exchange Language for Flood Risk Communication

Abstract

Flooding is one of the most common natural disasters. There are extensive amounts of studies on understanding and predicting flooding to support preparedness and response. It is critical to share and communicate flood forecasting and modeling datasets generated by different systems and organizations. Most of the organizations share flood risk data for operational purposes with limited metadata and structure. However, there is no unified standard for exchanging flood forecast and alert data with various stakeholders and automated systems. This paper proposes a data communication specification, Flood Markup Language (FloodML), to extensively describe and exchange flood forecasts and alerts with corresponding stakeholders. FloodML can be used in a wide variety of data sharing use cases and needs for emergency management, research and modeling communities, and the general public.

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