精准刻画气候变暖背景下山地冰川的空间演化，是高寒区水资源精细化评估的重要基础。本研究基于耦合开放全球冰川模型（OGGM）的“物理-地形双驱动”冰川形态矢量重构算法，集成中国第二次冰川编目数据集、SRTM数字高程模型数据及CMIP6多模式气象强迫集合，系统模拟了祁连山地区2020-2100年间在四种共享社会经济路径（SSP126、SSP245、SSP370和SSP585）下的冰川矢量数据集，时间分辨率为5年，数据总量约0.98 GB。与基于2020年和2025年卫星遥感影像的冰川边界解译结果及OGGM原始输出相比，本数据集在模拟精度方面表现更优，各情景下重构的冰川面积平均绝对误差稳定控制在0.0068 km²以内，典型冰川的几何边界与实际地形发育及退缩机制高度契合。数据集同时提供了冰川编码、冰川面积、OGGM原始模拟冰川面积、最高海拔、中值海拔、最低海拔、坡向、质心坐标及流域编码等多维属性信息。本数据集可为祁连山地区冰川变化监测、冰川融水模拟及水资源管理等相关研究提供可靠的数据支撑。", "ds_source": "", "ds_process_way": "", "ds_quality": "", "ds_acq_start_time": "2020-01-01 00:00:00", "ds_acq_end_time": "2100-12-31 00:00:00", "ds_acq_place": "祁连山地区", "ds_acq_lon_east": 102.2, "ds_acq_lat_south": 37.36666666666667, "ds_acq_lon_west": 95.01666666666667, "ds_acq_lat_north": 39.6, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 704206885, "ds_files_count": 0, "ds_format": "*.shp", "ds_space_res": "30米", "ds_time_res": "5年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "0de792c6-ab24-4215-a67c-602c3c10fc26.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "None", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": null, "ds_serv_phone": null, "ds_serv_mail": null, "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 0, "publish_time": "2026-08-24 10:58:08", "last_updated": "2026-08-24 11:05:29", "protected": false, "protected_to": "2027-02-20 00:00:00", "lang": "zh", "cstr": "11738.11.ncdc.glacier.db7720.2026", "i18n": { "en": { "title": "Vector Dataset of Simulated Glacier Boundaries for the Qilian Mountains (2020–2100)", "ds_format": "*.shp", "ds_source": "", "ds_quality": "", "ds_ref_way": "", "ds_abstract": "
Accurately characterizing the spatial evolution of mountain glaciers under climate warming is fundamental to the refined assessment of water resources in alpine regions. Here, we present a glacier vector dataset for the Qilian Mountains, generated using a \"physics-topography dual-driven\" vector reconstruction algorithm coupled with the Open Global Glacier Model (OGGM). The dataset integrates the Second Chinese Glacier Inventory, SRTM digital elevation model, and CMIP6 multi-model meteorological forcing, covering the period 2020–2100 under four SSP scenarios (SSP126, SSP245, SSP370, and SSP585) at 5-year intervals, with a total volume of ~0.98 GB. Validation against satellite-interpreted glacier boundaries for 2020 and 2025 and raw OGGM outputs demonstrates that our dataset achieves higher accuracy, with mean absolute errors of reconstructed glacier areas consistently below 0.0068 km² across all scenarios and geometric boundaries of typical glaciers closely matching observed topographic and retreat patterns. The dataset provides multidimensional attributes, including glacier code, area, OGGM-simulated area, elevation statistics (maximum, median, minimum), aspect, centroid coordinates, and watershed code. This dataset offers robust support for glacier monitoring, meltwater simulation, and water resource management in the Qilian Mountains region.", "ds_time_res": "", "ds_acq_place": "Qilian mountain area", "ds_space_res": "", "ds_projection": "", "ds_process_way": "", "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_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "allow_update_data": false, "ds_topic_tags": [ "冰川边界", "祁连山", "OGGM", "CMIP6" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "祁连山" ], "ds_time_tags": [ 2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055, 2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067, 2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079, 2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091, 2092, 2093, 2094, 2095, 2096, 2097, 2098, 2099, 2100 ], "ds_contributors": [ { "true_name": "姚晓军", "email": "xj_yao@nwnu.edu.cn", "work_for": "西北师范大学地理与环境科学学院", "country": "中国" }, { "true_name": "赵嘉威", "email": "2023222966@nwnu.edu.cn", "work_for": "西北师范大学地理与环境科学学院", "country": "中国" }, { "true_name": "孙美平", "email": "sunmeiping1982@163.com", "work_for": "西北师范大学地理与环境科学学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "姚晓军", "email": "xj_yao@nwnu.edu.cn", "work_for": "西北师范大学地理与环境科学学院", "country": "中国" } ], "ds_managers": [ { "true_name": "姚晓军", "email": "xj_yao@nwnu.edu.cn", "work_for": "西北师范大学地理与环境科学学院", "country": "中国" } ], "category": "冰川" }