作为第二大人类部门用水，高质量的工业用水格网数据对于水资源研究和管理至关重要。中国工业用水格网数据（China Industrial Water Withdrawal dataset，\nCIWW）基于超过 40 万家企业数据、月度工业产品产量数据和连续工业用水统计数据制作得到的一套1965-2020年逐月中国工业用水数据集，其空间分辨率为\n0.1°和 0.25°。数据集包括工业用水、企业数量和企业生产总值（辅助数据）等变量，可被用于水文、地理学、环境、可持续发展等方面科学研究。", "ds_source": "
数据来源为《中国经济普查年鉴》(省级工业取水量、工业产出)、《中国工业企业数据库》（企业地理位置、产值）、《中国工业产品产量数据库》（工业产品月生产量），以及《中国水资源公报》和(Zhou et al, 2020, PNAS)的工业用水量数据。", "ds_process_way": "
首先通过2008年企业分布数据、经济普查年鉴中分省分部门的工业用水量和工业产值计算得到分省分部门工业用水效率和工业产品产量数据，得到了2008年逐月工业用水数据。\n然后结合中国水资源公报和相关文献中省级工业用水数据，以2008年工业用水的时空格局作为基础分配工业用水数据，最终得到1965-2020年逐月工业用水的格网数据。\n详细方法见High-resolution mapping of monthly industrial water withdrawal in China from 1965 to 2020 (Hou et al, 2024, ESSD).", "ds_quality": "
将数据集与统计数据记录和其他数据集进行了验证，结果表示在时间尺度和空间尺度上都与统计数据具有一致性，相比已有工业用水数据有更好的精度。\n
详细比较内容及结果见High-resolution mapping of monthly industrial water withdrawal in China from 1965 to 2020 (Hou et al, 2024, ESSD)。", "ds_acq_start_time": "1965-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 135.25, "ds_acq_lat_south": 17.75, "ds_acq_lon_west": 74.0, "ds_acq_lat_north": 54.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 1207150504, "ds_files_count": 8, "ds_format": "txt,excel,nc", "ds_space_res": "0.1度,0.25度", "ds_time_res": "月", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "cfd4bb7e-d984-4ac3-a6e0-1bcf6d76a460.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a4dd5849-78f2-44c5-b0f1-3450e952b2a2", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45", "170.55" ], "quality_level": 3, "publish_time": "2024-07-05 12:07:28", "last_updated": "2026-01-13 16:44:39", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.FIGSHARE.DB6533.2024", "i18n": { "en": { "title": "The China industrial water withdrawal dataset (CIWW)", "ds_format": "", "ds_source": "
The data sources include the China Economic Census Yearbook (provincial industrial water intake and industrial output), the China Industrial Enterprise Database (geographical location and output value of enterprises), the China Industrial Product Output Database (monthly production volume of industrial products), as well as industrial water consumption data from the China Water Resources Bulletin and (Zhou et al, 2020, PNAS).", "ds_quality": "
The dataset was validated against statistical data records and other datasets, and the results showed consistency with statistical data on both temporal and spatial scales, with better accuracy compared to existing industrial water use data.\n
The detailed comparison content and results can be found in the High resolution mapping of monthly industrial water with drawings in China from 1965 to 2020 (Hou et al, 2024, ESSD).", "ds_ref_way": "", "ds_abstract": "
As the second largest human sector in water use, high-quality industrial water grid data is crucial for water resource research and management\nReason is crucial. China Industrial Water Withdrawing Dataset,\nBased on data from over 400000 enterprises, monthly industrial product output data, and continuous industrial water use statistics, a monthly Chinese industrial water use dataset from 1965 to 2020 was developed by CIWW, with a spatial resolution of\n0.1 ° and 0.25 °. The dataset includes variables such as industrial water use, number of enterprises, and gross domestic product (auxiliary data), which can be used for scientific research in hydrology, geography, environment, sustainable development, and other fields.
", "ds_time_res": "月", "ds_acq_place": "China", "ds_space_res": "0.1度,0.25度", "ds_projection": "", "ds_process_way": "Firstly, based on the distribution data of enterprises in 2008, the industrial water consumption and industrial output value of each province and sector in the economic census yearbook, the industrial water efficiency and industrial product output data of each province and sector were calculated, and the monthly industrial water consumption data for 2008 was obtained.\nThen, combining the provincial industrial water use data from the China Water Resources Bulletin and relevant literature, the spatial and temporal pattern of industrial water use in 2008 was used as the basis for allocating industrial water use data, and finally, the monthly grid data of industrial water use from 1965 to 2020 was obtained.\nFor detailed methods, please refer to High resolution mapping of monthly industrial water with drawings in China from 1965 to 2020 (Hou et al, 2024, ESSD)", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "ds_topic_tags": [ "中国", "工业用水", "网格数据" ], "ds_subject_tags": [ "地理学", "水文学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 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": "侯程程", "email": "cch@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" }, { "true_name": "李琰", "email": "yanli@bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "侯程程", "email": "cch@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "侯程程", "email": "cch@mail.bnu.edu.cn", "work_for": "北京师范大学", "country": "中国" } ], "category": "其他" }