{"id":"5d6c3095-edd7-46f5-a71f-772e17c0af38","title":"“一带一路”沿线国家径流系数和径流深数据（2015）","title_en":"Dataset of Runoff Coefficient and Runoff Depth in Belt and Road Region (2015)","serial":"","user_limit":"为尊重知识产权、保障数据作者的权益、扩展数据中心的服务、评估数据的应用潜力，请数据使用者在使用数据所产生的研究成果中（包括公开发表的论文、论著、数据产品和未公开发表的研究报告、数据产品等成果），明确注明数据来源和数据作者。对于转载（二次或多次发布）的数据，作者还须注明原始数据来源。","instructions":"Geotiff格式，使用GIS软件打开","description":"水资源估算的主要思路是使用径流系数和径流影响因子（包括气候、地形、土地利用、土壤等）建立机器学习模型，然后再根据模型估算的径流深和降水数据计算出成径流系数。首先，基于全球公开资料，建立径流深和地形、气候、土壤、土地利用的多种机器学习模型，评估不同模型的模拟精度和有效性，选择最优模型用于径流深估算。最后，利用最优模型估算并生成“一带一路”地区径流深分布，根据2015年的降水分布数据，计算得到径流系数分布。","doi":"10.11888/Hydro.tpdc.271013","projection":"","language":"zh","share_type":"online","east":10.0,"west":180.0,"south":-15.0,"north":85.0,"scale":null,"crs":null,"filesize":3.7,"share_policy":"a","ts_created":"2020-10-25T00:00:00+08:00","doi_type":"拥有自主知识产权","ts_updated":"2021-04-19T19:36:27.324780+08:00","time_description":"","datas_group":3,"time_description_en":"","data_format":null,"project":[11],"specials":["f2a78cde-1c98-4241-94dc-7532eba32b80"],"cite":null,"review_status":5,"review_invite":[{"user_name":"郑东海","username":"XDA20100100","email":"zhengd@itpcas.ac.cn","is_cancel_expert":false}],"review_editor":{"id":42421,"last_login":"2022-04-08T15:16:51.670544+08:00","username":"任慧霞","email":"510727846@qq.com","is_active":true,"is_staff":true,"user_name":"任慧霞"},"data_sources":null,"temporal_resolution":"Yearly","spatial_resolution":"1km - 10km","license":"Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","fund":[6],"subtopics":{"metadata":"5d6c3095-edd7-46f5-a71f-772e17c0af38","three_pole":null,"third_pole":"XDA20010201"},"username":"XDA20010201","review_time":null,"protected_duration":null,"protected_describe":null,"is_important":false,"hit_count":1984}