基于ICESat-2激光雷达测高仪数据及自仿射理论推导的经验方程，估算了2022年青藏高原面积大于0.01 km²的湖泊体积。研究发现模拟湖泊体积与实地测量值吻合良好，最大湖深的平均绝对百分比误差为8.0%，湖泊体积的平均绝对百分比误差为19.7%。据估算，2022年青藏高原面积大于0.01 km²的湖泊总蓄水量为1043.69±341.31 km³，其中约70%（~734.8 km³）的湖泊蓄水量集中于内高原（羌塘高原）。该数据基于遥感方法初步厘清了青藏高原湖泊蓄水量，为未来湖泊水量变化预测、水文平衡分析及水资源管理提供了重要数据支撑。
", "ds_source": "1、ICESat-2 ATL03测高数据：从Earthdata平台（https://search.earthdata.nasa.gov）获得的2019年至2023年可用的ICESat-2 ATL03（v006）数据（图1b）。与加工后的高级产品相比，ATL03保留了更多的原始光子。ATL03数据集中应用了大气延迟、地理定位、固体地球潮汐和其他地球物理和介质校正。\n2、原位测深数据：原位测深数据是从 TP 总共 35 个湖泊中整理的。\n3、附加数据：2000—2022年间Landsat TM/ETM+/OLI时间序列划定的动态湖泊边界用于计算湖泊面积随时间的变化，并过滤研究区域的ICESat-2 ATL03数据。
", "ds_process_way": "在本数据中，我们开发了一种利用ICESat-2穿透光子重建清水湖泊水深的新方法。该方法依托三阶段数学函数（反正切-线性-反正切）来表征湖泊水深剖面。随后采用分层抽样方案在青藏高原（TP）范围内选取60个湖泊，运用此方法生成其水深数据。结合自仿射理论，估算了青藏高原其他湖泊的体积，并获得了2022年湖泊总蓄水量。本研究提出的方法可低成本生成湖泊水深信息，青藏高原湖泊蓄水量数据集不仅有助于深入理解湖泊水体的空间分布特征，更能为湖泊形态学与生态学研究提供基础数据支撑。
", "ds_quality": "本研究提出的模型有效利用了湖面以上的湖岸地形，并将ICESat-2/ATLAS的穿透特性与水下地形参考相结合，将平均APE降低至19.7%。与使用简单的线性或二次函数，或直接使用样条函数将数字高程模型向下延伸相比，三阶段数学函数使收敛效果更接近湖床自然地形过渡，尽管复杂性增加，但可能提高了重建水深测量的精度。本研究中模拟水体体积的精度低于“骨架插值法”所得结果，但高于数值模拟法所得精度。
", "ds_acq_start_time": "2022-01-01 00:00:00", "ds_acq_end_time": "2022-12-31 00:00:00", "ds_acq_place": "青藏高原", "ds_acq_lon_east": 104.67222222222223, "ds_acq_lat_south": 25.99361111111111, "ds_acq_lon_west": 73.49888888888889, "ds_acq_lat_north": 39.825833333333335, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 22752443, "ds_files_count": 2, "ds_format": "shp", "ds_space_res": "", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "f49c6fbe-0b05-4fdf-8887-f8d699876a34.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "09314967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.55" ], "quality_level": 3, "publish_time": "2025-10-31 14:48:29", "last_updated": "2026-01-14 11:00:59", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB6986.2025", "i18n": { "en": { "title": "Reconstruction of Lake Depth Measurement Data in the Qinghai Tibet Plateau Using ICESat-2 Photon Counting Laser Altimeter Technology (2022)", "ds_format": "shp", "ds_source": "1. ICESat-2 ATL03 altimetry data: from Earthdata platform（ https://search.earthdata.nasa.gov ）Obtained ICESat-2 ATL03 (v006) data available from 2019 to 2023 (Figure 1b). Compared to processed high-end products, ATL03 retains more original photons. The ATL03 dataset applies atmospheric delay, geolocation, solid earth tides, and other geophysical and medium corrections.\n2. In situ depth measurement data: The in-situ depth measurement data was compiled from a total of 35 lakes in TP.\n3. Additional data: The dynamic lake boundaries delineated by Landsat TM/ETM+/OLI time series from 2000 to 2022 are used to calculate the changes in lake area over time and filter the ICESat-2 ATL03 data of the study area.
", "ds_quality": "The model proposed in this study effectively utilizes the shoreline terrain above the lake surface and combines the penetration characteristics of ICESat-2/ATLAS with underwater terrain reference, reducing the average APE to 19.7%. Compared with using simple linear or quadratic functions, or directly extending the digital elevation model downwards using spline functions, three-stage mathematical functions make the convergence effect closer to the natural terrain transition of the lake bed. Although the complexity increases, it may improve the accuracy of reconstructing water depth measurements. The accuracy of simulating water volume in this study is lower than that obtained by skeleton interpolation method, but higher than that obtained by numerical simulation method.
", "ds_ref_way": "", "ds_abstract": "Based on ICESat-2 LiDAR altimeter data and empirical equations derived from self affine theory, the volume of lakes with an area greater than 0.01 km ² on the Qinghai Tibet Plateau in 2022 was estimated. The study found that the simulated lake volume matched well with the measured values on site, with an average absolute percentage error of 8.0% for the maximum lake depth and 19.7% for the lake volume. It is estimated that the total water storage capacity of lakes with an area greater than 0.01 km ² on the Qinghai Tibet Plateau in 2022 will be 1043.69 ± 341.31 km ³, of which about 70% (~734.8 km ³) of the lake water storage capacity is concentrated in the inner plateau (Qiangtang Plateau). This data, based on remote sensing methods, has preliminarily clarified the water storage capacity of lakes on the Qinghai Tibet Plateau, providing important data support for predicting future changes in lake water volume, analyzing hydrological balance, and managing water resources.
", "ds_time_res": "年", "ds_acq_place": "Qinghai-Tibet Plateau", "ds_space_res": "", "ds_projection": "", "ds_process_way": "In this dataset, we have developed a new method for reconstructing the water depth of clear lakes using ICESat-2 penetrating photons. This method relies on a three-stage mathematical function (arctangent linear arctangent) to characterize the lake water depth profile. Subsequently, a stratified sampling scheme was used to select 60 lakes within the Qinghai Tibet Plateau (TP) and generate their water depth data using this method. Based on the self affine theory, the volumes of other lakes on the Qinghai Tibet Plateau were estimated, and the total water storage capacity of the lakes in 2022 was obtained. The method proposed in this study can generate lake water depth information at low cost. The Qinghai Tibet Plateau lake water storage dataset not only helps to deeply understand the spatial distribution characteristics of lake water bodies, but also provides basic data support for lake morphology and ecology research.
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "ds_topic_tags": [ "湖泊测深", "湖泊体积", "ICESat-2 激光测高仪" ], "ds_subject_tags": [ "水文学" ], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原" ], "ds_time_tags": [ 2022 ], "ds_contributors": [ { "true_name": "张国庆", "email": "guoqing.zhang@itpcas.ac.cn", "work_for": "中国科学院青藏高原研究所", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "张国庆", "email": "guoqing.zhang@itpcas.ac.cn", "work_for": "中国科学院青藏高原研究所", "country": "中国" } ], "ds_managers": [ { "true_name": "张国庆", "email": "guoqing.zhang@itpcas.ac.cn", "work_for": "中国科学院青藏高原研究所", "country": "中国" } ], "category": "水文" }