Application and Evaluation of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in Poorly Gauged Regions in Western China

Abstract

The temporal and spatial differentiation of the underlying surface in East Asia is complex. Due to a lack of meteorological observation data, human cognition and understanding of the surface processes (runoff, snowmelt, soil moisture, water production, etc.) in the area have been greatly limited. With the Heihe River Basin, a poorly gauged region in the cold region of Western China, selected as the study area, three meteorological datasets are evaluated for their suitability to drive the Soil and Water Assessment Tool (SWAT): China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), Climate Forecast System Reanalysis (CFSR), and Traditional Weather Station (TWS). Resultingly, (1) the runoff output of CMADS + SWAT mode is generally better than that of the other two modes (CFSR + SWAT and TWS + SWAT) and the monthly and daily Nash–Sutcliffe efficiency ranges of the CMADS + SWAT mode are 0.75–0.95 and 0.58–0.77, respectively; (2) the CMADS + SWAT and TWS + SWAT results were fairly similar to the actual data (especially for precipitation and evaporation), with the results produced by CMADS + SWAT lower than those produced by TWS + SWAT; (3) the CMADS + SWAT mode has a greater ability to reproduce water balance than the other two modes. Overestimation of CFSR precipitation results in greater error impact on the uncertainty output of the model, whereas the performances of CMADS and TWS are more similar. This study addresses the gap in the study of surface processes by CMADS users in Western China and provides an important scientific basis for analyzing poorly gauged regions in East Asia.

Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China

“…Their runoff simulations were similar to the observed runoff, indicating that good performance had been achieved (as shown in Table 6). Other studies have also verified the high accuracy of CMADS in runoff simulation over the Qinghai-Tibet Plateau [27], Heihe River Basin [28], and Korean Peninsula [23]. Overall, the runoff simulations from CFSR + SWAT were similar to the observed runoff, but obvious overestimation of runoff could be seen in August 2012, and underestimation in August 2013 ( Figure 6).…”

“…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.…”

“…The reanalysis dataset CMADS could be a complementary meteorological data source for OBS. Meng et al [28] and Gao et al [31] found that CMADS performed as well as OBS in runoff simulations, while CFSR performed the worst. Wang et al [29] showed that both CMADS and CFSR could not be used as supplements to OBS.…”

“…Both of them can be conveniently applied in the Soil and Water Assessment Tool (SWAT) model, which is the hydrological model used in this study, to assess the performance of reanalysis products in runoff simulation. Some studies have compared CFSR with CMADS in West [27][28][29][30] and Central [31] China. For instance, Liu et al [27] found that CMADS performed better than CFSR and OBS in the hydrological modelling results in the Qinghai-Tibet Plateau.…”

Analysis of Non-Point Source Pollution Features of Chao River Basin Based on the CMADS-Driven SWAT Model

“…Data are the kernel of models, and the quality of the driving data directly affects the simulation results. The China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model has achieved good performance in simulation of hydrological and water quality conditions in basins [7][8], but it was mostly applied to studies in basins in western China, and rarely was it used in research in the northern area in China. Through a case study on the Chao River basin in the upper reach of Miyun Reservoir, we employed the CMADS V1.0-driven SWAT model to simulate NPS pollution in the basin, and analyzed its applicability in the basin to explore the spatial-temporal distribution pattern of NPS pollution in the basin and contributions of different pollutants.…”