Status and Future of Integrating Satellite Monitoring of Global Floods
Abstract
Satellite observations and models are being used to monitor floods in real-time on a global scale. Examples are shown of current individual approaches of satellite-based estimation of inundation and other parameters related to flooding and their strengths and weaknesses. The March 2019 flood in Mozambique associated with Cyclone Idai is a focus in this context utilizing output from the Global Flood Monitoring System (GFMS) and other products, including inundation estimates from SAR and optical data. and from passive microwave observations. The GFMS estimates real-time flood detection, streamflow estimates and inundation for most of the globe and is driven by satellite-based precipitation. Validation results for this case and others indicate the satellite rain estimates may be underestimating these peak events.
The satellite-based estimates of rainfall were difficult to evaluate in this case because of the lack of surviving ground measurements. NWP forecasts were significantly larger than estimated with IMERG (1000 mm vs. 600 mm) and the satellite rain also seemed to be lower (especially at the high end) than available ground data in the larger region. The 1 km resolution inundation maps calculated by GFMS are compared to SAR estimates. In terms of latency GFMS was generating inundation estimates as soon as it started flooding about 15 March, but the first SAR estimates were produced by 20 March. The accuracy of the GFMS estimates were evaluated both for simultaneous instantaneous estimates on 19-20 March and also with a time-integrated (15-19 March) GFMS inundation map. The results show significant underestimation of the SAR-based flood area, although this is ameliorated by the use of time integration. These effects seem to be related to a combination of the underestimation of the rainfall amounts and a hydrologic phase error. The GFMS inundation maps are also compared to other products, including an estimate based on passive microwave data and terrain information. Plans for possible integration of these types of estimates to provide a consistent method for users to access the best data quickly are described.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.H43N2247A
- Keywords:
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- 1855 Remote sensing;
- HYDROLOGY