Assessing the capability and accuracy of SWOT satellite river observations in China

doi:10.11947/j.AGCS.2026.20250484

Abstract

Abstract:

This study evaluates the observation capability and accuracy of the SWOT wide-swath altimetry satellite for monitoring river water levels and water level changes in China. Within a 21-day revisit cycle, SWOT can observe 97.39% of river reaches in China at least once. Validation against in situ water level data from 301 hydrological gauge stations demonstrates that SWOT achieves a mean absolute error (MAE) of 0.35 m for monitoring river water level variations in China, with an overall correlation coefficient greater than 0.9. Results across different basins indicate that SWOT exhibits higher monitoring accuracy in the Songhua-Liaohe, Haihe, Huaihe, and Yellow River basins (MAE<0.3 m), while relatively larger errors are observed in the Pearl River and Yangtze River basins. To address phase unwrapping errors near dams caused by spatial discontinuity of water levels, this study employs a correction method based on low-coherence water body identification and optimal integer ambiguity determination, which spatially separates upstream and downstream water bodies and iterates through different integer ambiguities to recover correct elevations. To address the asymmetric noise distribution characteristic of narrow rivers, this study proposes a multi-level adaptive filtering (MAF) algorithm based on spatial continuity testing, which identifies anomalous points through k-nearest neighbor spatial continuity testing and adaptively removes outliers based on skewness characteristics. Validation at 10 test stations shows that after phase unwrapping correction and MAF algorithm processing, the average MAE decreased from 1.73 m to 0.32 m. This research validates the reliability of SWOT satellite for river water level monitoring variations in China, providing a technical approach for large-scale, high-precision hydrological parameter acquisition, with important reference value for water resource management and flood disaster monitoring.

Key words: SWOT satellite, satellite altimetry, river water level, phase unwrapping, denoising

CLC Number:

P228

Hao Lu, Wei Feng, Xiaobing Wang, Wei Chen, Min Zhong. Assessing the capability and accuracy of SWOT satellite river observations in China[J]. Acta Geodaetica et Cartographica Sinica, 2026, 55(7): 1240-1253.

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URL: http://xb.chinasmp.com/EN/10.11947/j.AGCS.2026.20250484

http://xb.chinasmp.com/EN/Y2026/V55/I7/1240

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误差来源	高程误差/cm
电离层信号	0.8
干对流层信号	0.7
湿对流层信号	4.0
径向轨道误差	1.6
KaRIn随机+系统误差	8.9
运动误差	0.8

流域	河段数	单个周期观测次数占比					河宽<50 m占比次
流域	河段数	0次	1次	2次	3次	4次	河宽<50 m占比次
长江流域	9737	2.63	22.73	66.53	7.89	0.23	18.61
珠江流域	3960	3.13	25.91	70.96	0	0	24.19
松辽流域	2518	2.46	15.85	40.63	30.10	10.96	23.11
西南诸河	2046	1.76	21.26	68.04	8.75	0.20	25.56
内陆河	1881	4.73	19.88	48.33	23.23	3.83	25.78
东南诸河	1530	1.18	23.14	72.88	2.81	0	16.27
淮河流域	1502	1.6	20.84	62.85	13.12	1.60	11.72
黄河流域	1489	1.68	25.12	57.56	13.57	2.08	16.59
海河流域	460	3.26	22.83	43.91	23.26	6.74	27.83

流域	水位变化的平均MAE/m	MAE标准差/m	最大MAE/m	最小MAE/m	站点数量
东南诸河	0.43	0.30	1.13	0.07	20
内陆河	0.46	0.40	1.32	0.07	8
松辽流域	0.20	0.14	0.50	0.05	17
海河流域	0.21	0.12	0.34	0.10	3
淮河流域	0.14	0.15	0.71	0.02	25
珠江流域	0.42	0.64	4.54	0.02	58
长江流域	0.41	0.52	3.05	0.02	129
黄河流域	0.29	0.27	1.02	0.04	41