raybet体育在线 院报 ›› 2025, Vol. 42 ›› Issue (6): 36-43.DOI: 10.11988/ckyyb.20240857

• 水资源 • 上一篇    下一篇

基于卫星测高的武汉市东湖水位变化监测

刘火胜1(), 汪海洪2(), 余乾慧1, 卢亮3, 秦鹏程4, 刘义兵1   

  1. 1 武汉市公共气象服务中心,武汉 430040
    2 武汉大学 测绘学院, 武汉 430079
    3 湖北省武汉市水文水资源勘测局, 武汉 430079
    4 武汉区域气候中心,武汉 430074
  • 收稿日期:2024-08-12 修回日期:2024-10-10 出版日期:2025-06-01 发布日期:2025-06-01
  • 通信作者:
    汪海洪(1976-),男,江西宁都人,副教授,博士,主要从事卫星测高理论及应用研究。E-mail:
  • 作者简介:

    刘火胜(1970-),男,湖北武汉人,高级工程师,主要从事天气预报和城市气象研究。E-mail:

  • 基金资助:
    国家自然科学基金项目(41974016); 海绵城市建设水系统科学湖北省重点实验室开放基金项目(武汉大学)(2022-04); 武汉市园林和林业局科技基金项目(WHGF2022A05); 湖北省自然科学基金项目(2023AFD098)

Water Level Variation Monitoring in East Lake, Wuhan Based on Satellite Altimetry

LIU Huo-sheng1(), WANG Hai-hong2(), YU Qian-hui1, LU Liang3, QIN Peng-cheng4, LIU Yi-bing1   

  1. 1 Wuhan Public Meteorological Service Center, Wuhan 430040, China
    2 School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
    3 Wuhan Hydrology and Water Resources Survey Bureau, Wuhan 430079, China
    4 Wuhan Regional Climate Center, Wuhan 430074, China
  • Received:2024-08-12 Revised:2024-10-10 Published:2025-06-01 Online:2025-06-01

摘要:

为验证卫星测高技术监测城市湖泊水位变化的能力,以武汉东湖为例评估Jason-3卫星测高数据的质量,比较ICE、重心偏移法和阈值法等重跟踪方法的效果,采用一种稳健的测高数据策略构建东湖2017—2022年湖水位时间序列,并结合气象数据分析湖水位变化特征。结果表明对于东湖Jason-3测高数据采用50%阈值的阈值法重跟踪精度最高,与水文实测水位相比均方根误差为0.108 m,相关系数为0.87。2017年9月至2022年3月,东湖水位稳定在19.5 m左右,变化幅度<0.5 m,月变化基本在0.2 m以内。东湖水位与降水量相关性差,没有明显的季节性变化,人为调控起着支配作用。研究结果展示了卫星测高技术用于城市湖泊水位变化监测的潜力。

关键词: 水位监测, 卫星测高, 城市湖泊, 波形重跟踪, 武汉东湖

Abstract:

[Objectives] Satellite altimetry has become a crucial method for monitoring lake water levels, yet significant challenges remain in its application to small lakes, particularly in complex urban environments. Currently, limited studies explore the effectiveness of satellite altimetry for monitoring variations of urban lake water levels. Using East Lake in Wuhan as a case study, this study evaluates the quality of Jason-3 satellite altimetry data, aiming to validate the capability of satellite altimetry in monitoring urban lake water level variations. [Methods] Based on the Jason-3 Sensor Geophysical Data Record (SGDR) products from 2017 to 2022, this study used two key parameters—pulse peakiness and waveform width—to first analyze the altimetry waveform characteristics of East Lake. In addition to the original range observations and ICE-retracked ranges provided by SGDR products, this study applied the Offset Center of Gravity (OCOG) and threshold methods for waveform retracking. Among them, the threshold retracking method selected eight threshold levels ranging from 20% to 90% (in 10% increments) to analyze the retracking performance under different thresholds. A robust coarse elimination strategy based on the Median Absolute Deviation (MAD) was employed to eliminate outliers from the water level observation data, followed by the calculation of periodic average water levels to construct the lake water level time series. To evaluate the quality of water level data by different methods, the range and standard deviation of water levels in each period, as well as the number of invalid periods, were statistically analyzed. Additionally, the accuracy of the results using different methods was verified using the measured data from hydrological stations. Finally, meteorological data (precipitation, evaporation) and a water balance model were integrated to quantify the contributions of natural and anthropogenic factors to East Lake’s water level variations. [Results] (1) Statistical analysis of pulse peakiness and waveform width from the lake surface altimetry echoes revealed that approximately 50% of East Lake’s waveforms exhibited specular reflections with distinct sharp peaks, while about 30% displayed complex shapes containing two or more peaks. (2) The results of accuracy validation using the on-site measured data of water levels showed that the 50% threshold retracking method achieved optimal performance, with a root mean square error (RMSE) of 0.108 m and a correlation coefficient of 0.87. (3) Based on the 50% threshold retracking method, and using Jason-3 data, the water level time series of East Lake from September 2017 to February 2022 was established. The results demonstrated that the lake water level remained stable around 19.5 m during this period, with annual fluctuations <0.5 m, monthly variations <0.2 m, and no pronounced seasonal pattern. Although precipitation was the primary water source, water levels showed extremely low correlation with precipitation (R=0.007), and weak negative correlation with evaporation (R=-0.44). According to the analysis of water balance, artificial regulation played a key role in the water level variations of East Lake. [Conclusions] (1) Jason-3 satellite altimetry data can effectively monitor urban lake water level variations, but requires careful data processing, including waveform retracking and outlier elimination. (2) Despite complex waveforms over urban lakes, retracking methods significantly improve altimetry accuracy. Compared with waveform retracking methods such as OCOG, ICE, and threshold method, the 50% threshold method is more suitable for urban lakes.

Key words: water level monitoring, satellite altimetry, urban lake, waveform retracking, East Lake in Wuhan

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