Monitoring water level changes in the middle and lower reaches of the Yangtze River using Sentinel-3A satellite altimetry data
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摘要: 河流水位是了解水循环和水资源变化状况的重要参数。新型雷达高度计技术是提取河流水位变化的有利工具。为了验证新型雷达高度计Sentinel-3A/SRAL数据监测河流水位的能力,提高其提取河流水位变化的精度,以长江中下游干流为研究对象,利用重心偏移法、阈值主波峰重跟踪算法(阈值取50%和80%)、重心主波形重跟踪算法和多回波波峰一致重跟踪算法对Sentinel-3A/SRAL L2级数据进行波形重跟踪,提取了长江中下游干流各区域2016—2021年间河流水位,并对比不同算法获取水位的精度,得到最优重跟踪算法,从而提取了12条轨道过境区域的水位变化信息,分析了水位变化规律。结果表明,重心偏移法算法是提取河流水位精度最好的重跟踪算法,各区域虚拟水位与实测水位相比具有最大相关系数(达0.968)、最小均方根误差(达0.680 m); 2016—2021年间长江中下游干流水位总体呈上升趋势,年内水位变化呈现明显的季节性。
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关键词:
- Sentinel-3A /
- 波形分类 /
- 波形重跟踪 /
- 长江 /
- 水位变化
Abstract: River levels serve as a critical parameter for understanding the changes in water cycles and water resources. An advanced Radar altimeter is a favorable tool for extracting the changes in river levels. This study aims to verify the ability of the Sentinel-3A/SRAL Radar altimeter to monitor river levels and improve the extraction accuracy of this Radar altimeter. With the main streams in the middle and lower reaches of the Yangtze River as the study area, this study conducted waveform retracking for the Sentinel-3A/SRAL L2 data using the center-of-gravity offset method, the primary peak threshold retracking algorithm (thresholds: 50% and 80%), the primary waveform centroid retracking algorithm, and the multiple-echo peak consistency retracking algorithm. Then, this study extracted the river levels during 2016—2021 in the study area and obtained the optimal retracking algorithm by comparing the accuracy of different algorithms. Based on the optimal retracking algorithm, this study extracted the water level changes in transit areas of 12 satellite orbits to analyze the water level change patterns. The results show that the center-of-gravity offset method is the optimal retracking algorithm for extracting river levels with the highest accuracy. Compared with the measured water levels, the water levels simulated using the center-of-gravity offset method exhibited the highest correlation coefficient (up to 0.968) and the smallest root mean square error (up to 0.680 m). During 2016—2021, the water levels in the study area generally showed an upward trend, with significant intra-annual seasonal changes.-
Key words:
- Sentinel-3A /
- waveform classification /
- waveform retracking /
- Yangtze River /
- water level change
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