ET（蒸散发）监测对农业水资源管理、区域水资源利用规划和社会经济可持续发展至关重要。传统监测ET方法的局限性主要在于无法做到大面积同时观测，只能局限于观测点上，因此人员设备成本相对较高，既不能提供面上的ET数据，也不能提供不同土地利用类型和作物类型的ET数据。
\n\n利用遥感可以做到ET的定量监测，遥感信息的特点是既能反映地球表面的宏观结构特性，又能反映微观局部的差异。由于地下水埋深、灌溉、管理等方面的差异，既使是相邻地块，真正的农业用水量会有很大的不同，而遥感监测以像元为基础，能够将作物蒸散量在空间上的差别监测出来，能更好地提供田块级的农业耗水信息。
\n\n本项目的目标是以干旱区陆表蒸散遥感估算为研究对象，针对蒸散模型参数化中的瓶颈问题，充分利用ETWatch方法和现有黑河的地面观测基础，围绕下垫面热力非均匀性的定量描述方法、地面能量项闭合修正、平流误差补偿、地表水分胁迫、大气参考高度确定等关键问题，研究多尺度-多源数据融合的陆表蒸散参数化方法，结合黑河典型区野外观测数据进行参数优化，形成黑河流域不同下垫面的参数集，提高流域尺度蒸散估算的可靠性、稳定性和时空连续性，建设黑河流域长时间序列的蒸散遥感数据集。
\n\n本数据为2000-2010年整个黑河流域分辨率为1公里的ET数据（第一版）。
", "ds_source": "（1）遥感影像数据
\n\n中低分辨率MODIS数据
\n\n低分辨率遥感数据，通过购买与网上免费下载收集形成2000-2010年的MODIS数据集。覆盖整个黑河流域1天的MODIS数据由4组文件组成，每组文件根据区域范围分割成2个文件。
\n\nFY-2数据
\n\n通过中国气象局国家卫星气象中心风云卫星遥感数据服务网站上获取到2005-2011年的风云卫星云分类产品数据，包括FY-2C和FY-2D两颗卫星的数据。云分类产品为标称格式，覆盖FY-2D全圆盘范围，分辨率与标称图一致，星下点分辨率为5KM。
\n\nFY-2C/D云分类产品可以较准确的完成 FY-2 整个观测区域云的分类，在云检测完成的基础上主要对高云部分进行分类，对于中低云由于目前探测能力的限制。对于高云可以准确的分出积雨云、密卷云、卷层云、高层云或雨层云等类别。
\n\n（2）气象数据
\n\n获取2010年覆盖整个黑河流域用于1公里分辨率ET监测的每日气象数据，包括风速、最高气温、最低气温、湿度、气压、太阳日照时数6个要素项。
", "ds_process_way": "ETWatch、SEBAL模型、SEBS模型、彭曼－蒙特斯公式
\n\n详情见文件说明文档
", "ds_quality": "根据盈科站2008年EC数据验证分析，发现计算值冬季偏小，夏季偏大，年误差为2.9%。
", "ds_acq_start_time": "2020-01-13 00:00:00", "ds_acq_end_time": "2020-01-13 00:00:00", "ds_acq_place": "黑河流域", "ds_acq_lon_east": 100.33055555555555, "ds_acq_lat_south": 38.765, "ds_acq_lon_west": 100.33, "ds_acq_lat_north": 38.76444444444444, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 55336804, "ds_files_count": 2, "ds_format": "Geotiff", "ds_space_res": "1000.0m", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "6181ee4b-a43e-4f3c-94ac-9d3ee9260167.png", "ds_thumb_from": 2, "ds_ref_way": "黑河计划数据管理中心，2000-2010年黑河流域蒸散发数据，国家冰川冻土沙漠科学数据中心(www.ncdc.ac.cn)，2020，doi：10.12072/ncdc.Westdc.db0021.2020", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "9c4867b1-5cb1-4de0-abeb-df42547bf41e", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": null, "quality_level": 3, "publish_time": "2020-10-13 16:46:05", "last_updated": "2020-10-13 16:46:05", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.Westdc.2020.700", "i18n": { "en": { "title": "Evapotranspiration data of Heihe River Basin from 2000 to 2010", "ds_format": "", "ds_source": "(1) Remote sensing image data
\nMODIS data with medium and low resolution
\nLow resolution remote sensing data were collected by purchasing and downloading online free of charge to form MODIS data set from 2000 to 2010. MODIS data covering the whole Heihe River Basin for one day is composed of four groups of files, each group of files is divided into two files according to the regional scope.
\nFY-2 data
\nThe cloud classification product data of FY-2C and FY-2D from 2005 to 2011 were obtained through the Fengyun satellite remote sensing data service website of National Satellite Meteorological Center of China Meteorological Administration. The cloud classification products are in nominal format, covering the whole FY-2D disk range. The resolution is consistent with the nominal map, and the resolution of sub star point is 5km.
\nFY-2C / D cloud classification products can accurately complete the cloud classification of FY-2 in the whole observation area. On the basis of cloud detection, the high cloud part is mainly classified. For the medium and low cloud, due to the limitation of the current detection ability, the cloud classification product of FY-2C / D can accurately complete the cloud classification of FY-2. For high clouds, it can be accurately divided into cumulonimbus, cirrus, cirrus, high-level cloud or rain layer cloud.
\n(2) Meteorological data
\nThe daily meteorological data covering the whole Heihe River Basin for 1 km resolution et monitoring in 2010 were obtained, including six elements: wind speed, maximum temperature, minimum temperature, humidity, air pressure and sunshine hours.
", "ds_quality": "According to the verification and analysis of EC data of Yingke station in 2008, it is found that the calculated value is smaller in winter and larger in summer, with an annual error of 2.9%.
", "ds_ref_way": "", "ds_abstract": "ET (evapotranspiration) monitoring is very important for agricultural water resources management, regional water resources utilization planning and socio-economic sustainable development. The limitation of traditional et monitoring method is that it can not be observed in large area at the same time, and it can only be limited to observation points. Therefore, the cost of personnel and equipment is relatively high. It can not provide the ET data on the surface, nor can it provide the ET data of different land use types and crop types.
\nThe quantitative monitoring of ET can be achieved by using remote sensing. The characteristics of remote sensing information are that it can not only reflect the macro structural characteristics of the earth surface, but also reflect the micro local differences. Due to the differences in groundwater depth, irrigation and management, even if it is adjacent plots, the real agricultural water consumption will be very different. Remote sensing monitoring based on pixel can monitor the spatial differences of crop evapotranspiration, and can provide better field level agricultural water consumption information.
\nThe objective of this project is to take the remote sensing estimation of land surface evapotranspiration in arid areas as the research object. Aiming at the bottleneck problem in the parameterization of evapotranspiration model, the etwatch method and the existing ground observation basis of Heihe River are fully used. The quantitative description method of thermal heterogeneity of underlying surface, the closure correction of surface energy, advection error compensation, surface water stress, and determination of atmospheric reference height are discussed In order to improve the reliability, stability and spatiotemporal continuity of evapotranspiration estimation at basin scale, a long-term evapotranspiration remote sensing data set of Heihe River Basin is constructed by optimizing the parameters of land surface with multi-scale and multi-source data fusion.
\nThis data is the first edition of ET data with resolution of 1 km in Heihe River Basin from 2000 to 2010.
", "ds_time_res": "年", "ds_acq_place": "Heihe River Basin", "ds_space_res": "1000.0m", "ds_projection": "", "ds_process_way": "Etwatch, SEBAL model, SEBS model, penman Montes formula
\nSee the documentation for details
", "ds_ref_instruction": " " } }, "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": [ "蒸散发", "ETWatch", "SEBS模型", "彭曼－蒙特斯公式", "SEBAL模型" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010 ], "ds_contributors": [ { "true_name": "黑河计划数据管理中心", "email": "westdc@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "" } ], "ds_meta_authors": [ { "true_name": "黑河计划数据管理中心", "email": "westdc@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "" } ], "ds_managers": [ { "true_name": "黑河计划数据管理中心", "email": "westdc@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "" } ], "category": "生态" }