A dataset of lake level changes in China using multi-altimeter data(2002-2023)
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Lake water levels are an important indicator of water balance and water cycles, and are essential for climate and environmental change studies and water resource evaluation. Currently, lake level measurements are scarce or inconsistent throughout the country, and traditional gauge measurements of many lakes are not feasible, so satellite altimetry is a vital alternative to gauge lake levels. However, the accuracy and sampling frequency of lake level time series are usually low because of time and space coverage limitations; therefore, it is necessary to utilize multi-altimeter data to monitor lake levels and obtain lake level changes over long time series. In this study, we extracted the water level changes in 988 lakes (>10 km2) in China between 2002 and 2023 based on ICESat/-2, Cryosat-2, Jason-1/2/3, and Sentinel-3A/3B altimetry data using waveform retracking, lake level extraction, lake level time series construction, the fusion of multi-altimeter lake level time series, and outlier removal. A total of 55% of the lakes in this dataset have been monitored for more than 10 years, and 34% have more than 12 times the annual average water level monitoring, and the mean RMSE of the fused lake levels reaches 0.332 m. This dataset has high spatiotemporal coverage and accuracy and can support the estimation of changes in lake water storage, analysis of lake level trends, plateau flooding, and the relationship between lake ecosystems and water resources.
湖泊水位是水量平衡与水循环的重要表征指标，对于气候变化与环境变化研究以及水资源评价而言不可或缺。当前，我国境内湖泊水位实测数据稀缺且标准不一，且多数湖泊难以开展传统水位站监测，因此卫星测高技术成为湖泊水位观测的重要替代方案。然而受时空覆盖范围限制，现有湖泊水位时间序列的精度与采样频率普遍偏低，因此需融合多源测高数据开展湖泊水位监测，以获取长时序的湖泊水位变化数据。本研究基于ICESat/-2、Cryosat-2、Jason-1/2/3及Sentinel-3A/3B等卫星测高数据，通过波形重跟踪、湖泊水位提取、水位时间序列构建、多源测高水位时间序列融合以及异常值剔除等技术流程，提取了2002年至2023年间我国988个面积大于10平方千米湖泊的水位变化数据。本数据集覆盖的湖泊中，55%的监测时长超过10年，34%的年平均监测频次高于12次，融合后湖泊水位的平均均方根误差（Root Mean Square Error，RMSE）可达0.332米。本数据集具备优异的时空覆盖度与精度，可支撑湖泊蓄水量变化估算、湖泊水位趋势分析、高原洪水研究以及湖泊生态系统与水资源间关联关系的相关研究。
