Toward a novel approach for assimilation of SAR-based flood observations in a fully coupled hydrological model

点击翻译按钮获取中文摘要

Flooding poses a significant risk to humanity. Thousands of people are displaced each year due to flooding, inaddition to destruction of infrastructure and agriculture. Satellite observations are increasingly being used forflood monitoring. Satellite-borne synthetic aperture radars (SARs) are a particularly appealing source ofobservations due to their ability to return meaningful information of the earth's surface during all weatherconditions. With increasing numbers of SAR systems in orbit, and growing data volumes, it is of interest todevelop methods to use these data in automated processes.One such process, known as data assimilation, combines observational data with output from a forecast modelto provide an improved initial condition for the forecast model. This is the method used to generate weatherforecasts. For flood forecasting, assimilation of water level observations (WLOs) from SAR imagery is arelatively new area. Previous studies have obtained the WLOs from SAR using a prescribed geometry of theground surface (bathymetry). The proposed research will use a fully coupled hydrological model in which thebathymetry evolves with the flood to develop a novel approach to retrieve and assimilate WLOs from SARdata. The long-term goal is to improve flood forecasts.