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DOI10.3390/w11040832
Profound Impacts of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS)
Meng, Xianyong1,2; Wang, Hao3; Chen, Ji2
发表日期2019
ISSN2073-4441
卷号11期号:4
英文摘要

As global warming continues to intensify, the problems of climate anomalies and deterioration of the water environment in East Asia are becoming increasingly prominent. In order to assist decision-making to tackle these problems, it is necessary to conduct in-depth research on the water environment and water resources through applying various hydrological and environmental models. To this end, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) has been applied to East Asian regions where environmental issues are obvious, but the stations for monitoring meteorological variables are not uniformly distributed. The dataset contains all of the meteorological variables for SWAT, such as temperature, air pressure, humidity, wind, precipitation, and radiation. In addition, it includes a range of variables relevant to the Earth's surface processes, such as soil temperature, soil moisture, and snowfall. Although the dataset is used mainly to drive the SWAT model, a large number of users worldwide for different models have employed CMADS and it is expected that users will not continue to limit the application of CMADS data to the SWAT model only. We believe that CMADS can assist all the users involved in the meteorological field in all aspects. In this paper, we introduce the research and development background, user group distribution, application area, application direction, and future development of CMADS. All of the articles published in this special issue will be mentioned in the contributions section of this article.


WOS研究方向Water Resources
来源期刊WATER
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/95372
作者单位1.CAU, Coll Resources & Environm Sci, Beijing 100094, Peoples R China;
2.Univ Hong Kong HKU, Dept Civil Engn, Pokfulam, Hong Kong 999077, Peoples R China;
3.China Inst Water Resources & Hydropower Res IWHR, Beijing 100038, Peoples R China
推荐引用方式
GB/T 7714
Meng, Xianyong,Wang, Hao,Chen, Ji. Profound Impacts of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS)[J],2019,11(4).
APA Meng, Xianyong,Wang, Hao,&Chen, Ji.(2019).Profound Impacts of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS).WATER,11(4).
MLA Meng, Xianyong,et al."Profound Impacts of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS)".WATER 11.4(2019).
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