Research on the quality screening method for satellite altimetry data——take Jason-3 data and Hongze Lake as an example
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Abstract:
This paper proposes a method based on data quality evaluation and extraction of water level to improve the steadiness of dat a quality of satellite altimetry in lakes and reservoirs area. We used Jason-3 satellite altimetry data and performed a case study in Hongze Lake area where the altimetric data quality was unsteady. Results showed that the accuracy of this method was obviously better than that of the traditional methods. The correlation coefficient between the satellite-derived water level and the gauged water level increased from 0.11 to 0.59, and the root mean square error was reduced from 2 m to 0.5 m, making the Jason-3 data more reliable for water level monitoring of lakes and reservoirs. In addition, for those periods with poor data quality, since the water level accuracy is gener ally low, they can be discarded based on the results of data quality evaluation. This can further improve the overall monitoring accuracy. The correlation coefficient can be increased to 0.9, and the root mean square error was reduced to 0.19 m. This is of great significance to building a precise capacity curve for the ungauged lakes and reservoirs.
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