SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Establishment and evaluation of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) 
Authors:Meng, X., H. Wang, C. Shi, Y. Wu and X. Ji 
Year:2018 
Journal:Water 
Volume (Issue):10 
Pages: 
Article ID:1555 
DOI:10.3390/w10111555 
URL (non-DOI journals): 
Model:none 
Broad Application Category:data or component development 
Primary Application Category:data and/or component contribution to SWAT or SWAT+ 
Secondary Application Category:none 
Watershed Description:none 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:We describe the construction of a very important forcing dataset of average daily surface climate over East Asia—the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool model (CMADS). This dataset can either drive the SWAT model or other hydrologic models, such as the Variable Infiltration Capacity model (VIC), the Soil and Water Integrated Model (SWIM), etc. It contains several climatological elements—daily maximum temperature (C), daily average temperature (C), daily minimum temperature (C), daily average relative humidity (%), daily average specific humidity (g/kg), daily average wind speed (m/s), daily 24 h cumulative precipitation (mm), daily mean surface pressure (HPa), daily average solar radiation (MJ/m2), soil temperature (K), and soil moisture (mm3/mm3). In order to suit the various resolutions required for research, four versions of the CMADS datasets were created—from CMADS V1.0 to CMADS V1.3. We have validated the source data of the CMADS datasets using 2421 automatic meteorological stations in China to confirm the accuracy of this dataset. We have also formatted the dataset so as to drive the SWAT model conveniently. This dataset may have applications in hydrological modelling, agriculture, coupled hydrological and meteorological modelling, and meteorological analysis. 
Language:English 
Keywords:CMADS; SWAT; East Asia; meteorological; hydrological