How well will SWOT observe global river basins?
Abstract
The Surface Water and Ocean Topography (SWOT) mission is designed to provide global observations of water surface elevation and slope from which river discharge can be estimated using a data assimilation system. This mission will provide increased spatial and temporal coverage compared to current altimeters, with an expected accuracy for water level elevations of 10 cm on rivers greater than 100 m wide. Within the 21-day repeat cycle, a river reach will be observed 2-4 times on average. Due to the relationship between the basin orientation and the orbit, these observations may not be evenly distributed in time, which can impact the derived discharge values. There is, then, a need for a better understanding of how the mission will observe global river basins. In this study, we investigate how SWOT will observe 32 global river basins and how the temporal sampling impacts the discharge estimated from assimilation. SWOT observations can be assimilated using the Inverse Streamflow Routing (ISR) model of Pan and Wood [2013] with a fixed interval Kalman smoother. Previous work has shown that the ISR assimilation method can be used to reproduce the spatial and temporal dynamics of discharge within many global basins: however, this performance was strongly impacted by the spatial and temporal availability of discharge observations. In this study, we apply the ISR method to basins with different geometries and crossing patterns for the future orbit. For each basin, three synthetic experiments are carried out. These are: (1) assimilating in-situ gauges only, (2) using in-situ gauges and SWOT-retrieved "gauges", and (3) using SWOT-retrieved "gauges" only. Results show that the model performance varies significantly across basins and is driven by the orientation, flow distance, and travel time in each. Based on these properties, we classify the "observability" of each basin and relate this to the performance of the ISR method. Finally, we attempt to improve the ISR performance in poorly observed basins by optimizing the locations and timing of observations used. By carefully considering the availability of SWOT observations, hydrologic data assimilation approaches like ISR can provide useful discharge estimates in sparsely gauged regions where spatially and temporally consistent discharge records are most valuable.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.H21L..08F
- Keywords:
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- 1855 Remote sensing;
- HYDROLOGYDE: 1856 River channels;
- HYDROLOGYDE: 4520 Eddies and mesoscale processes;
- OCEANOGRAPHY: PHYSICALDE: 4594 Instruments and techniques;
- OCEANOGRAPHY: PHYSICAL