globalchange  > 气候变化事实与影响
DOI: 10.3390/w11040832
WOS记录号: WOS:000473105700202
论文题名:
Profound Impacts of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS)
作者: Meng, Xianyong1,2; Wang, Hao3; Chen, Ji2
通讯作者: Meng, Xianyong ; Wang, Hao ; Chen, Ji
刊名: WATER
ISSN: 2073-4441
出版年: 2019
卷: 11, 期:4
语种: 英语
英文关键词: CMADS ; impact ; hydrological modeling ; SWAT
WOS关键词: RIVER-BASIN ; SNOWMELT ; RUNOFF
WOS学科分类: Water Resources
WOS研究方向: Water Resources
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.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/132705
Appears in Collections:气候变化事实与影响

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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

Recommended Citation:
Meng, Xianyong,Wang, Hao,Chen, Ji. Profound Impacts of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS)[J]. WATER,2019-01-01,11(4)
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