湖泊既是陆地水资源的重要储蓄场所，也是区域和全球水文循环系统的重要水汽源，是气候变化的重要载体和指示器。为了评估ICESat-2/ATLAS（ice, cloud and land elevation satellite-2/advanced topographic laser altimeter system）测高数据在湖泊水位估计中的精度和应用潜力，以地处青藏高原地区的青海湖为例，基于2018年10月31日至2019年11月8日期间ATL13产品提取的青海湖湖区瞬时水位数据，并结合水文观测、LEGOS（Laboratoire d’Etudes en GéOphysique et ceanographie Spatiales）水位和风浪观测资料，验证了ATL13产品在青海湖的湖泊日均、月均水位估计精度。结果表明：ATL13产品中6束脉冲的光斑脚点高程与高程实测值的绝对误差为0.07 m，标准误差为0.18 m；2018年10月至2019年11月青海湖日均水位呈上升趋势，2018年10月青海湖月均水位估计值为3 195.75 m，2019年11月的月均水位估计值为3 196.21 m，年内湖泊月均水位上升了0.46 m；青海湖的LEGOS水位和水位观测显示，时段内月均水位分别增加了0.29±0.20 m和0.58±0.10 m；ATL13产品估计的湖泊月均水位与水位观测值较为一致，与LEGOS水位的绝对误差为0.17 m，可能受到观测时段、数据质量和空间异质性影响。
英文摘要:
Lakes provide not only storage for terrestrial water resources, but also water source for regional and global hydrological cycle systems, they are important carriers and indicators of climate change. In order to evaluate the accuracy and application potential of lake water level estimated by ICESat-2/ATLAS (ice, cloud and land elevation satellite-2/advanced topographic laser altimeter system) altimetry data, the mean daily water level change of Qinghai Lake, Tibet Plateau was estimated by ATL13 product from October 31, 2018 to November 8, 2019. The accuracy of daily and monthly instantaneous lake water level estimated by ATL13 product were verified using the datasets from the local hydrological stations and LEGOS (Laboratoire d’Etudes en Géophysique et ceanographie Spatiale). The results showed that the absolute error between laser footprints of the ATL13 product and the measured elevation was 0.07 m, and the mean standard error between them was 0.18 m. The daily mean water level of Qinghai Lake was rising during the study period. The estimated monthly mean lake water level was 3,195.75 m in October， 2018 and 3,196.21 m in November， 2019, which increased by 0.46 m in only one year. According to the datasets from LEGOS and hydrological stations, the water level increased by 0.29±0.20 m and 0.58±0.10 m, respectively. So, the monthly mean lake water level estimated by ATL13 product was consistent with the measured data of the hydrological stations; however, the absolute error between the estimated water level and that of LEGOS was 0.17 m, which might have been caused by the continuity of the observation period, data quality and spatial heterogeneity of LEGOS.