本数据集是第一个提供中国流域气象时间序列和流域属性的数据集。该数据集由数字高程模型(DEM)导出的所有流域边界组成，该模型是全球流域数据集。GDBD以高分辨率(100 m-1 km)导出，与中国现有的全球流域数据具有良好的地理一致性。其中汇编了不同的数据源，包括土壤、土地覆盖、气候、地形和地质。该数据集还包括了每个流域从1990年到2020年共31年的气象数据。
\n数据集由中国流域属性与气象数据集和HydroMLYR两个部分组成。第一个数据集提供了中国流域的日气象时间序列和120多个属性。日气象时间序列包括降水、温度、蒸散发、风速、地表温度、气压、湿度、日照时数和潜在蒸散发。流域属性包括地形、气候、水文、土地覆盖、地质和土壤等属性。HydroMLYR（黄河流域机器学习水文数据集）包括每日气象时间序列、标准化周平均流量和102个集水区的120多个属性。", "ds_source": "
数据来源于Zenodo网站https://zenodo.org/records/5729444", "ds_process_way": "
汇编不同的数据源，包括土壤、土地覆盖、气候、地形和地质，以开发数据集。基于Penman方程推导各流域的潜在蒸散发时间序列。", "ds_quality": "
数据质量较好。", "ds_acq_start_time": "1990-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 138.3, "ds_acq_lat_south": 18.166666666666668, "ds_acq_lon_west": 76.0, "ds_acq_lat_north": 52.25, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 3696765123, "ds_files_count": 2, "ds_format": "shp,json,txt,excel", "ds_space_res": "", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "15dc74da-78bb-4c6e-a61a-1f6a82b069e8.png", "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": [ "170.15", "170.55" ], "quality_level": 3, "publish_time": "2023-11-27 15:59:16", "last_updated": "2026-01-14 11:11:30", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.ZENODO.DB4093.2023", "i18n": { "en": { "title": "CCAM: China Basin Attributes and Meteorological Dataset", "ds_format": "shp,json,txt,excel", "ds_source": "
Data sourced from Zenodo website https://zenodo.org/records/5729444", "ds_quality": "
The data quality is good.", "ds_ref_way": "", "ds_abstract": "
This dataset is the first to provide meteorological time series and basin attributes for Chinese river basins. This dataset consists of all watershed boundaries derived from the Digital Elevation Model (DEM), which is a global watershed dataset. GDBD is exported with high resolution (100 m-1 km) and has good geographical consistency with existing global watershed data in China. It compiles different data sources, including soil, land cover, climate, terrain, and geology. This dataset also includes 31 years of meteorological data for each watershed from 1990 to 2020.
\nThe dataset consists of two parts: the Chinese Basin Attributes and Meteorological Dataset and HydroMLYR. The first dataset provides daily meteorological time series and over 120 attributes for Chinese river basins. The daily meteorological time series includes precipitation, temperature, evapotranspiration, wind speed, surface temperature, air pressure, humidity, sunshine hours, and potential evapotranspiration. Watershed attributes include terrain, climate, hydrology, land cover, geology, and soil properties. HydroMLYR (Yellow River Basin Machine Learning Hydrological Dataset) includes daily meteorological time series, standardized weekly average flow, and over 120 attributes for 102 catchment areas.
", "ds_time_res": "年", "ds_acq_place": "China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Compile different data sources, including soil, land cover, climate, terrain, and geology, to develop a dataset. Derive potential evapotranspiration time series for each watershed based on Penman equation.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 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, "ds_topic_tags": [ "中国流域", "气象数据", "蒸散发", "土地覆盖" ], "ds_subject_tags": [ "大气科学", "水文学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 ], "ds_contributors": [ { "true_name": "金瑾", "email": "jinjinhao@21cn.com", "work_for": "黄河水利科学研究", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "金瑾", "email": "jinjinhao@21cn.com", "work_for": "黄河水利科学研究", "country": "中国" } ], "ds_managers": [ { "true_name": "敏玉芳", "email": "myf@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "水文" }