本数据集包含黑河流域上游2000年1月至2015年12月融雪径流深逐日数据，以tiff格式保存。完全开放共享。数据通过分布式寒区水文模型GBEHM和遥感参数标定方法，利用长时间序列高空间分辨率积雪遥感数据，为模型提供标定的目标函数以及驱动数据；利用地面调查得到的积雪属性数据，为模拟系统提供更为准确的参数信息，进而估算了2000年至2015逐年融雪径流系数数据。文件名：cs_yyyy.tiff，字段说明：cs指代融雪径流系数，yyyy为年，例如2010；mm为月，例如三月为03.
", "ds_source": "数据源原始数据包括气象台站数据、再分析资料数据、遥感积雪面积数据以及水文径流数据。气象台站数据来自中国积雪调查项目第一课题；遥感积雪面积数据来自中国积雪调查项目第二课题；再分析资料数据为使用WRF数据自主模拟；水文径流数据来自寒旱区科学数据中心。
", "ds_process_way": "数据通过分布式寒区水文模型GBEHM和遥感参数标定方法，利用长时间序列高空间分辨率积雪遥感数据，为模型提供标定的目标函数以及驱动数据；利用地面调查得到的积雪属性数据，为模拟系统提供更为准确的参数信息，进而估算了2000年至2015逐年融雪径流系数数据。
", "ds_quality": "该数据是在GBEHM水文模型并结合黑河流域气象要素资料进行模拟的结果上进行的进一步统计分析结果。由于降水数据与融雪径流数据都经过相应的验证，此融雪径流系数数据是相对合理的。同时在数据处理过程中，对异常值进行了粗差剔除。
", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2015-12-31 00:00:00", "ds_acq_place": "黑河流域上游", "ds_acq_lon_east": 101.17916666666667, "ds_acq_lat_south": 37.71944444444445, "ds_acq_lon_west": 98.57416666666666, "ds_acq_lat_north": 39.13138888888889, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 2324405, "ds_files_count": 18, "ds_format": "TIF", "ds_space_res": "1000", "ds_time_res": "日", "ds_coordinate": "无", "ds_projection": "GCS_WGS_1984", "ds_thumbnail": "f382f1bc-635c-4d8d-91fa-e95ec1a951ab.jpg", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "使用申明建议采用如下方式：数据来源于科技基础性工作专项“中国积雪特性及分布调查（2017FY100503）”\r\n致谢方式参考以下规范：“感谢科技基础性工作专项“中国积雪特性及分布调查（2017FY100503）提供数据支撑。”", "ds_from_station": null, "organization_id": "aba68fe5-65d3-41b1-b036-bc274a834b5e", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [], "quality_level": 3, "publish_time": "2021-11-19 16:04:44", "last_updated": "2023-03-06 13:01:50", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.isnow.db2502.2022", "i18n": { "en": { "title": "snow runoff coefficient maps of Heihe basin during 2000-2015", "ds_format": "TIF", "ds_source": " <pre><code>\nThe original data source includes meteorological station data, reanalysis data, remote sensing snow area data and hydrological runoff data. The data of meteorological stations are from the first subject of China snow survey project; Remote sensing snow area data comes from the second project of China snow survey project; The reanalysis data is independent simulation using WRF data; The hydrological runoff data are from the scientific data center of cold and arid areas.
", "ds_quality": " <pre><code>\nThe data is the result of further statistical analysis based on the simulation results of gbehm hydrological model combined with meteorological element data of Heihe River Basin. Because the precipitation data and snowmelt runoff data have been verified, the snowmelt runoff coefficient data is relatively reasonable. At the same time, in the process of data processing, the outliers are eliminated.
", "ds_ref_way": "", "ds_abstract": " <pre><code>\nThis data set contains the daily data of snowmelt runoff depth in the upper reaches of Heihe River Basin from January 2000 to December 2015, which is saved in TIFF format. Fully open sharing.\n Through the distributed hydrological model gbehm and remote sensing parameter calibration method, the long-time series and high spatial resolution snow remote sensing data are used to provide the calibration objective function and driving data for the model; Using the snow attribute data obtained from the ground survey, more accurate parameter information is provided for the simulation system, and then the annual snowmelt runoff coefficient data from 2000 to 2015 are estimated.\n File name: CS_ Yyyy.tiff, Field Description: CS refers to snowmelt runoff coefficient, yyyy is year, for example, 2010; Mm is the month, for example, March is 03
", "ds_time_res": "日", "ds_acq_place": "Upper reaches of Heihe River Basin", "ds_space_res": "1000", "ds_projection": "", "ds_process_way": " <pre><code>\nThrough the distributed hydrological model gbehm and remote sensing parameter calibration method, the long-time series and high spatial resolution snow remote sensing data are used to provide the calibration objective function and driving data for the model; Using the snow attribute data obtained from the ground survey, more accurate parameter information is provided for the simulation system, and then the annual snowmelt runoff coefficient data from 2000 to 2015 are estimated.
", "ds_ref_instruction": " The following methods are recommended for use statement: the data are from the special \"survey on snow characteristics and distribution in China (2017fy100503)\" for basic work of science and technology\r\nFor the way of acknowledgement, please refer to the following specifications: \"thank the special project for basic work of science and technology\" China snow characteristics and Distribution Survey (2017fy100503) for providing data support. \"" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC 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, "ds_topic_tags": [ "黑河流域", "融雪径流系数", "积雪调查" ], "ds_subject_tags": [], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域上游" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015 ], "ds_contributors": [ { "true_name": "牛莉婷", "email": "", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "李弘毅", "email": "lihongyi@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "王建", "email": "wjian@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "李弘毅", "email": "lihongyi@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "李弘毅", "email": "lihongyi@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": "积雪" }