Establishment and Evaluation of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS)

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.

Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China

“…CMADS, developed by Prof. Xianyong Meng from China Agricultural University (CAU), was based on Local Analysis and Prediction System/Space-Time Multiscale Analysis System (LAPS/STMAS) and was constructed using loop nesting of data, projection of resampling models, and bilinear interpolation [28,32,33]. CMADS uses the six-hourly reanalysis components of the European Centre for Medium-Range Weather Forecasts (ECMWF) as its basic background fields and assimilates the regular raw station data and data from satellites and radars.…”

Assessing the Impact of Reservoir Parameters on Runoff in the Yalong River Basin using the SWAT Model

“…CMADS V1. 0 (spatial range 0 • N to 65 • N, 60 • E to 160 • E; spatial resolution 1/3 • ; temporal range 2008-2016) spatially divides the whole of East Asia into 300 × 195 grid points, a total of 58,500 sites; each site contains elements for daily average temperature, daily high/low temperature, daily precipitation, daily average solar radiation, daily average air pressure, daily specific humidity, and daily average wind speed [23,37]. Soil properties and land use types determine the runoff generation and confluence characteristics of different hydrological units, and they are also the basis for the definition of hydrological response units (HRU) in the SWAT model.…”

Moisture Distribution in Sloping Black Soil Farmland during the Freeze–Thaw Period in Northeastern China

“…We The soil temperature data of the sunny slope is more correlated with CMADS-ST, which coincides with the selection of the sunny slope in the wild slope farmland as the test Site 2. The monitored hourly data can be found in the freeze-thaw cycle with the time of day, melting during the day, and freezing at night (refer to Figure 3, the sunny slope soil experienced 39 freeze-thaw cycles, and the shady slope soil 47 cycles); however, the data period is short and the monitoring points are limited; CMADS-ST daily data can only see a large freeze-thaw cycle in the winter of the yearly cycle (refer to Figure 12); however, CMADS has a lot of spatiotemporal data, applied to a wide range of areas with a long series [11,31,33,[38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54].Using fixed-point monitoring of refined soil temperature, soil moisture content, precipitation, temperature, nitrogen and phosphorus of nutrients, spatiotemporal CMADS data can be better promoted and applied.…”

“…Soil moisture has great impacts on food security, human CMADS has been used successfully in different basins, such as the Heihe River Basin, Juntanghu Basin, Manas River Basin, and Han River Basin, indicating good applicability of CMADS in East Asia [38][39][40][41][42][43][44][45][46][47][48][49][50]. However, the relative studies mainly focused on the surface hydrological process and meteorological data, whereas the application of the CMADS-ST to soil temperature and soil moisture distribution has been rarely studied, especially in the black soil zone [51][52][53][54].…”