Flood Markup Language – A standards-based exchange language for flood risk communication

Abstract

Floods are one of the most frequently occurring natural disasters. There are numerous studies devoted to comprehending and forecasting flooding in order to aid in preparedness and response. It is critical to share and communicate datasets generated by various systems and organizations for flood forecasting and modeling. The majority of organizations share limited metadata and details for flood risk data to support research and operational activities. However, there is no standardized way for various stakeholders and automated systems to exchange flood forecast and alert data. This article proposes the Flood Markup Language (FloodML) as a data communication specification for extensively describing and exchanging flood forecasts and alerts with corresponding stakeholders. FloodML is applicable to a broad range of data sharing use cases and requirements for emergency management, the research and modeling communities, and the general public.