4.7 Article

INPPTR: An improved retracking algorithm for inland water levels estimation using Cryosat-2 SARin data

Journal

JOURNAL OF HYDROLOGY
Volume 613, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.jhydrol.2022.128439

Keywords

Satellite altimetry; Cryosat-2 SARin; INPPTR; Inland water; Water levels

Funding

  1. National Natural Science Foundation of China [41404031]
  2. State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology [SKLGED2022-3-5]
  3. Beijing Key Laboratory of Urban Spatial Information Engineering [20210206]

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The study introduces a new retracking algorithm, INPPTR, which improves the accuracy of waveform data and can effectively process water levels in regions with complex terrain.
As an important technology for measuring water levels, satellite altimetry has been widely using in the lake, river, and wetland in the past two decades. However, the waveform pollution limits its application in areas with complex topography, the accuracy of the existing retracking algorithms need to be further improved. In this study, a new retracking algorithm, named Improved Narrow Primary Peak Threshold Retracking algorithm (INPPTR), based on Narrow Primary Peak Threshold Retracking algorithm (NPPTR) is presented. This retracking algorithm eliminates the noise in the waveform, extracts more accurate main peaks of the waveform, and per-forms Gaussian fitting on the main peaks with serious waveform pollution. Finally, the more stable water levels in areas with complex terrain can be obtained from Cryosat-2 Synthetic Aperture Radar Interferometer (SARin) waveform. To verify the accuracy of retracking algorithms, the water level time series of eight lakes and one river were retrieved using INPPTR and other three retracking algorithms (NPPTR, NPPOR and MWaPP), then were compared to the in-situ data. For Qinghai Lake, Namco Lake, Selin Lake, Zhair Namco Lake, Issyk Lake, Great Salt Lake, Tahoe Lake and Great Slave Lake, where SARin mode is used, and the root mean squared errors (RMSE) obtained by INPPTR are 18.09 cm, 21.69 cm, 20.48 cm, 34.82 cm, 17.39 cm, 39.68 cm, 26.25 cm and 18.43 cm, respectively. Compared with NPPTR, the RMSE of INPPTR is reduced by 9.91 %, 14.83 %, 7.62 %, 14.74 %, 6.70 %, 4.11 %, 105.37 % and 25.02 %, respectively. For the Amazon River, the RMSE of INPPTR is 58.24 cm, compared with the other three retracking algorithms, the RMSE obtained by INPPTR is the lowest as well. In summary, the accuracy of INPPTR is significantly higher than the other three retracking algorithms, and INPPTR can process Cryosat-2 SARin data effectively and provide more stable and effective water levels, laying the foundation for long-term, high-accuracy water levels monitoring of inland water bodies with complex terrain.

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