China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) (Annual report – 2016)
China MeteorologicalAssimilation Driving Datasets for the SWAT model (CMADS)
(Annual report – 2016)
By Xianyong Meng
China Institute of Water Resources and Hydropower Research
Translate by Hongjing Wu & Xianyong Meng
Research associate, NRPOP Lab, Faculty of Engineering and AppliedScience, Memorial University of Newfoundland, Canada.
CMADS group, Beijing, China
Due to thelarge areas and differences of climate conditions and the lack ofmeteorological data in China, there are many challenges for research on surfacewater in hydrologic cycle and the associated driven force. Currently,China is facing the pressures from both water resource scarcity and waterpollutions. The consequences of water pollution problem have been obviouslyrevealed in recent years. Due to the low frequencies and small number of monitoringfor non-point source pollutions, it becomes the challenge to understand the continuousspatial distributions of non-point source pollution in China.
China MeteorologicalAssimilation Driving Datasets (CMADS) is developed based on China Land DataAssimilation System (CLDAS) and provide high resolution and quality meteorologicaldata for researchers. Applying CMADS can significantly reduce themeteorological input uncertainty for non-point source models and improve theperformance of non-point source modeling, since water resources and non-pointsource pollution can be more accurately localized. Besides, researchers canmake use of high resolution time series data from CMADS for spatial andtemporal scale analysis of meteorological data. CMADS present a basic andstandard meteorological data system, and researchers can conduct the related researchusing the same meteorological source for better and further comparison studiesin the future. We expect that CMADS can provide the reliable data forresearchers with confidence and convenience.
February, 12, 2017
Rejuvenating thecountry through science and technology, the essential data and information areessential. I am glad to see our work can be shared with different colleaguesfor the research purposes. CMADS datasets have been developed under a year, andhave been applied to different areas. I hope all the science and technology colleaguescan make use of this datasets for their research.
Chinese Academy of Engineering academician: Hao Wang
February, 12, 2017
CMADS has been released for over 10 months.From April 2016, we began to share this datasets on “National Earth System ScienceData Sharing Infrastructure” (http://westdc.westgis.ac.cn/).We have received 732 requests nationally and 14985 page views till Feb 12,2017. From the statistics, the requests reached the peak on May, 2016 (138persons/month). Around August, 2016 (around summer vacation time), the requestshave reached the first peak (30 persons/month), and then the number of requestsis fluctuated.
Figure1 The number of applications in 2016
In order tounderstand the distribution of CMADS Chinese user, we have randomly picked 708application forms from researchers and analyzed them. The most requests arefrom six provinces/cities, including Beijing (130 requests), Shaanxi (76 requests),Hubei (72 requests), Guangdong (48 requests), Gansu (47 requests) and Jiangsu(28 requests). The other requests from: Xinjiang, Hunan, Henan, Shandong,Chongqing, Jilin, Inner Mongolia, Zhejiang, Jiangxi, Sichuan, Yunnan, Shanghai,Heilongjiang, Tianjin, Hebei, Liaoning, Shanxi, Anhui, Guizhou, Fujian,Guangxi, Qinghai, Ningxia. There are no requests from following provinces: Macao,Nanhai, Taiwan, Tibet, Hongkong (Figure 3).
Figure2 The distribution of CMADS Chinese users
Figure3 The distribution of CMADS Chinese users
We also summarizedthe interested study areas of the Chinese CMADS users, the results showed thatnorthwestern area, southwestern area, north China, and northeastern areas aremost interested areas. However, the number of traditional meteorological stationsin these areas is less than that in Central China, Eastern China, and SouthernChina areas.
Figure4 The interested study areas in CMADS Chinese users
Figure5 The distribution of CMADS Chinese users
The six mostinterested study areas include Gansu (63 requests), Qinghai (46 requests),Xinjiang (45 requests), Beijing (44 requests), Tibet (38 requests). Other interestedprovinces include, Heilongjiang, Shaanxi, Inner Mongolia, Hebei, Guangdong,Yunnan, Shandong, Anhui, Hunan, Jiangxi, Hubei, Tianjin, Chongqing, Liaoning,Henan, Ningxia, Zhejiang, Sichuan, Jilin, Shanghai, Shanxi, Jiangsu, Guangxi.Fujian, Guizhou, Hainan. We also record different research areas where CMADS wereapplied (Figure 6).
Figure6 CMADSusers research areas
The results showedthat the most research areas where CMADS was applied mainly include: waterresource modeling (23%), eco-hydrology study (20%), nonpoint source pollutionresearch (19%), and climate change (7%). Other research areas include:assistance for remote sensing monitoring (3%), precipitation data collection(3%), teaching purposes (3%), groundwater research (2%), hydrological modelingin cool regions (2%), calculations for drought index (2%), Human activitiesimpacts on surface runoff (2%), Parameters uncertainty analysis forhydrological models (2%), mathematical modeling research (2%), otherhydrological studies (2%), PM 2.5 concentration research (1%), SWAT water andsalt transport (1%), hailstone disaster monitoring and prediction (1%), urbaninland inundation research (1%), multiple factor analysis for meteorologicaldata (1%), water quality modeling in cold regions (1%), troposphere delaymodeling (1%), technological products research (1%), solar radiation research(1%), and evapotranspiration research (1%).
In order to show the differences and features of the research, this report doesnot classify characteristic features of different research into major classification.For example, the hydrological modeling and water quality modeling in coldregions were not differentiated into water resource modeling and nonpointsource pollution, separately.
CMADS Users from:
Anqing Normal University
BaoJi University of Arts and Sciences
Beijing Jingshui River (Beijing) Engineering Consulting Co. Ltd.
Beijing Normal University
Beijing University of Technology
Beijing Wright Cyber Technology Services Ltd.
Central South Electric Power Design Institute
Changjiang Water Resources Commission
Changsha University of Science and Technology
Chengdu University of Technology
China Academy of Forestry Sciences
China Agricultural University
China Institute of water resources and Hydropower Research
China Three Gorges University
China University of Geosciences (Wuhan)
China University of Petroleum (Hua Dong)
Chinese Research Academy of Environmental Sciences
East China Normal University
Gansu Agricultural University
Gansu Meteorological Bureau Public Service Center
Guangzhou Institute of Geography
Guizhou Meteorological Bureau
Harbin Institute of Technology
Hebei university of engineering
Henan Polytechnic University
Huazhong University of Science and Technology
Hunan University of Science and Technology
Hunan University of Technology
Inner Mongolia Agricultural University
Inner Mongolia University
Institute of Geographical Sciences and resources
Jiangxi Institute of soil and water conservation
Jiangxi Normal University
Jobon garden Limited by Share Ltd
kunming university of science and technology
Langfang urban and rural planning and Design Institute
Nanchang Institute of Technology
Nanjing Normal University
nanjing university of information science and technology
North China Electric Power University
North China University of Water Resources and Electric Power
Northeast Agricultural University
Northeast Forestry University
Northeast Institute of geography and agricultural ecology, Chinese Academy of Sciences
Northeast Normal University
Northwest Agriculture and Forestry University
Pearl River Water Resources Commission
PLA 65061 unit
Research and development center of State Forestry Administration
Research Center for Eco Environmental Sciences; Chinese Academy of Sciences
Research Institute of water transport, Ministry of transport
Shaanxi Normal University
Shang Zheng (Beijing) Information Technology Co., Ltd.
Shenzhen Institute of advanced technology, Chinese Academy of Sciences
Southern China Environmental Science Research Institute
Sun Yat-sen University
The Yellow River survey planning and Design Co., Ltd.
University of Electronic Science and technology of China
Water Resources Protection Bureau
Xi'an Jiao Tong University
Xi'an University of technology
Xianyang Normal University
Xinjiang Institute of ecology and geography, Chinese Academy of Sciences
Yantai Institute of coastal zone, Chinese Academy of Sciences
Yuxi normal university