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Special Issue "Application of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in East Asia"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management and Governance".

Deadline for manuscript submissions: 31 December 2018

Special Issue Editors

Guest Editor
Prof. Dr. Hao Wang

State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin & China Institute of Water Resources and Hydropower Research, No. 1 Fuxing Road, Beijing, 100038, China
Website | E-Mail
Interests: allocation of water resources; water resource management
Guest Editor
Dr. Xianyong Meng

State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin & China Institute of Water Resources and Hydropower Research,No. 1 Fuxing Road, Beijing, 100038, China
Website | E-Mail
Interests: atmospheric data assimilation; hydrological modeling; land surface model assimilation

Special Issue Information

Dear Colleagues,

Due to spatial differences of climate conditions and the lack of meteorological data in East Asia, there are many challenges to conducting research on surface water in the hydrologic cycle. In addition, East Asia is facing pressure from both water resource scarcity and water pollution. The consequences of water pollution problems have been attracting public conerns in recent years. Due to the low frequencies and difficulty in monitoring non-point source pollutions, it becomes challenging to understand the continuous spatial distributions of non-point source pollution mechanisms in East Asia. China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) were developed and provided high resolution and quality meteorological data for the community. Applying CMADS can significantly reduce the meteorological input uncertainty and improve the performance of non-point source pollution modeling, since water resources and non-point source pollution can be more accurately localized. In addition, researchers can make use of high resolution time series data from CMADS for spatial and temporal scale analysis of meteorological data. Over the past few years, the CMADS data set has received worldwide attention from applicants such as the United States, Germany, Russia, Italy, India, South Korea, etc.

This Special Issue on “Application of the China Meteorological Assimilation Driving Datasets  for the SWAT model (CMADS) in East Asia” invites papers that report recent advances in the modeling of water quality and quantity in watersheds using CMADS and the hydrological model on a wide range of topics. These include, but are not limited to, water resource modeling, hydrological ecology, evolution and regulation of water ecological footprint, evolution of water resources and insurance, non-point source pollution, meteorological analysis, meteorological verification, atmospheric and hydrological coupling studies, changes in water resources under climate change, optimal operational  of reservoirs, water footprint assessment  and water cycle in arid and cold regions. We encourage submissions based on theoretical, computational and field studies that involve multiple hydrologic domains and interactions, as well as contributions that demonstrate novel applications.

Prof. Dr. Hao Wang
Dr. Xianyong Meng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • CMADS
  • Climate Change
  • Ecology
  • Hydrology
  • Meteorology
  • Natural Hazard
  • Pollution
  • SWAT
  • Sustainability

Published Papers (2 papers)

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Editorial

Jump to: Research

Open AccessEditorial Significance of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) of East Asia
Water 2017, 9(10), 765; doi:10.3390/w9100765
Received: 26 August 2017 / Revised: 16 September 2017 / Accepted: 30 September 2017 / Published: 8 October 2017
Cited by 1 | PDF Full-text (187 KB) | HTML Full-text | XML Full-text
Abstract
The high degree of spatial variability in climate conditions, and a lack of meteorological data for East Asia, present challenges to conducting surface water research in the context of the hydrological cycle. In addition, East Asia is facing pressure from both water resource
[...] Read more.
The high degree of spatial variability in climate conditions, and a lack of meteorological data for East Asia, present challenges to conducting surface water research in the context of the hydrological cycle. In addition, East Asia is facing pressure from both water resource scarcity and water pollution. The consequences of water pollution have attracted public concern in recent years. The low frequency and difficulty of monitoring water quality present challenges to understanding the continuous spatial distributions of non-point source pollution mechanisms in East Asia. The China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) was developed to provide high-resolution, high-quality meteorological data for use by the scientific community. Applying CMADS can significantly reduce the meteorological input uncertainty and improve the performance of non-point source pollution models, since water resources and non-point source pollution can be more accurately localised. In addition, researchers can make use of high-resolution time series data from CMADS to conduct spatial- and temporal-scale analyses of meteorological data. This Special Issue, “Application of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in East Asia”, provides a platform to introduce recent advances in the modelling of water quality and quantity in watersheds using CMADS and hydrological models, and underscores its application to a wide range of topics. Full article

Research

Jump to: Editorial

Open AccessArticle Evaluation and Hydrological Simulation of CMADS and CFSR Reanalysis Datasets in the Qinghai-Tibet Plateau
Water 2018, 10(4), 513; doi:10.3390/w10040513
Received: 11 March 2018 / Revised: 9 April 2018 / Accepted: 10 April 2018 / Published: 20 April 2018
PDF Full-text (3388 KB) | HTML Full-text | XML Full-text
Abstract
Multisource reanalysis datasets provide an effective way to help us understand hydrological processes in inland alpine regions with sparsely distributed weather stations. The accuracy and quality of two widely used datasets, the China Meteorological Assimilation Driving Datasets to force the SWAT model (CMADS),
[...] Read more.
Multisource reanalysis datasets provide an effective way to help us understand hydrological processes in inland alpine regions with sparsely distributed weather stations. The accuracy and quality of two widely used datasets, the China Meteorological Assimilation Driving Datasets to force the SWAT model (CMADS), and the Climate Forecast System Reanalysis (CFSR) in the Qinghai-Tibet Plateau (TP), were evaluated in this paper. The accuracy of daily precipitation, max/min temperature, relative humidity and wind speed from CMADS and CFSR are firstly evaluated by comparing them with results obtained from 131 meteorological stations in the TP. Statistical results show that most elements of CMADS are superior to those of CFSR. The average correlation coefficient (R) between the maximum temperature and the minimum temperature of CMADS and CFSR ranged from 0.93 to 0.97. The root mean square error (RMSE) for CMADS and CFSR ranged from 3.16 to 3.18 °C, and ranged from 5.19 °C to 8.14 °C respectively. The average R of precipitation, relative humidity, and wind speed for CMADS are 0.46; 0.88 and 0.64 respectively, while they are 0.43, 0.52, and 0.37 for CFSR. Gridded observation data is obtained using the professional interpolation software, ANUSPLIN. Meteorological elements from three gridded data have a similar overall distribution but have a different partial distribution. The Soil and Water Assessment Tool (SWAT) is used to simulate hydrological processes in the Yellow River Source Basin of the TP. The Nash Sutcliffe coefficients (NSE) of CMADS+SWAT in calibration and validation period are 0.78 and 0.68 for the monthly scale respectively, which are better than those of CFSR+SWAT and OBS+SWAT in the Yellow River Source Basin. The relationship between snowmelt and other variables is measured by GeoDetector. Air temperature, soil moisture, and soil temperature at 1.038 m has a greater influence on snowmelt than others. Full article
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