Description:

Flood monitoring, prediction, analysis and management are global needs. Science and technological advancements have led to the development of new monitoring and predictive tools that leverage the collection and synthesis of observational data into modeling frameworks. These advancements have produced a research and development environment that is rapidly changing with a growing number of centers that are producing useful flood monitoring and predictive tools. This session invites contributions from all sectors of the AMS and broader hydrologic community whose work focuses on: (1) the development of flood-monitoring and prediction tools (models, assimilation of observations, and methodologies to create and improve hydrologic representation of flood processes), (2) the analysis of floods and (3) lessons learned from managing floods from scientific and societal perspectives. 

We are particularly interested in submissions focused on the current state and future of continental and global scale hydrologic monitoring and prediction. Advancements in computing power and improved methodologies have measurably improved flood monitoring and have made running distributed hydrologic models at small spatial scales, on the order of 1–10 km2 spatial resolution, more feasible, with forecast lead times of up to a week or more. We welcome papers on current continental and global scale hydrologic forecasting systems with analyses of model performance compared to ground-truthed observations.The importance of these systems are underscored by the emergence of the Global Flood Partnership (GFP), which aims at the “development of flood observational and modeling infrastructure, leveraging on existing initiatives for better predicting and managing flood disaster impacts and flood risk globally.” The success of the GFP can directly benefit many countries where flood risk is poorly managed, but is critical to humanitarian assistance efforts. Significant questions surround the practical limits of continental and global scale hydrologic predictions that are useful and meaningful to communities’ efforts in Disaster Risk Reduction (DRR).

Submitters:  Thomas E. Adams III, NHDRR, U.S. Agency for International Development, Blacksburg, VA and Chandana Gangodagamage, Earth System Science Interdisciplinary Center (ESSIC), Univ. of Maryland, College Park, College Park, MD