Evaluation of Hydrological Application of CMADS in Jinhua River Basin, China

Zhou, Zhenghui; Gao, Xichao; Yang, Zhiyong; Feng, Jie; Meng, C. J.; Xu, Zhi

doi:10.3390/w11010138

Cited by 10 publications

(4 citation statements)

References 49 publications

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“…The findings of this study are different from those of previous studies, which reported that SWAT model driven by CMADS have a better performance in the research basin (X. Zhou et al, 2019). Base on Fig.…”

Section: Streamflow Simulation Results Of Different Datasetscontrasting

confidence: 99%

Application of Meteorological Element Combination-Driven SWAT Model based on Meteorological Datasets in Alpine catchment: A case study in the Yellow River Source Region (China)

Gu¹,

Wu²,

Liu³

et al. 2020

Preprint

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Reanalysis meteorological datasets have been widely used for hydrological simulation research in areas where meteorological stations are scarce. However, most of them focus on the applicability of datasets to basin or hydrological model and pay little attention to the influence of meteorological elements of dataset on hydrological modeling. In this study, the precipitation, temperature and solar radiation from three meteorological datasets, gauge dataset (GD), the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS), and Climate Forecast System Reanalysis (CFSR), were cross-combined with multiple scenarios to drive SWAT models in Yellow River Source Region (YRSR). After a comprehensive comparison of all the scenarios, the main conclusions are as follows: (1) replacing precipitation data has a large impact on streamflow simulation of SWAT model, and using observed precipitation from sparse stations consistently yielded better performance than using precipitation from CMADS and CFSR. (2) In the scenarios adopting observed precipitation as input, using temperature from CMADS and CFSR datasets yielded better performance than using observed temperature. (3) replacing solar radiation has slight impact on the streamflow simulation, and the solar radiation of CFSR is more suitable for hydrological simulation than that of CMADS in YRSR. (4) the SWAT model driven by different meteorological datasets shows that the runoff simulation of GD with CFSR solar radiation data (S6) is optimal with "very good" performance, while the simulation performance of CMADS and CFSR are poor with clearly underestimation for CMADS and significantly overestimation for CFSR, especially in the dry season. These result indicated that the element combination method of the meteorological dataset has been proven to be useful in YRSR, which provides a new insight for hydrological simulation research in areas where meteorological stations are scarce.

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Section: Streamflow Simulation Results Of Different Datasetscontrasting

confidence: 99%

Application of Meteorological Element Combination-Driven SWAT Model based on Meteorological Datasets in Alpine catchment: A case study in the Yellow River Source Region (China)

Gu¹,

Wu²,

Liu³

et al. 2020

Preprint

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“…Apparently, using GD (even with sparse coverage) as input to drive SWAT resulted in the best daily streamflow simulation in the YRSR [Figure 6(d)], followed by CFSR [Figure 7(b1)] and CMADS [Figure 7(a1)]. The findings of this study differ from those of previous studies, which reported that the SWAT models driven by CMADS have a better performance in the research basin (Gao et al 2018b;Zhou et al 2019). However, the performance of CMADS and CFSR was poor, with clear underestimation (PBIAS!52.3%) for CMADS and overestimation (PBIAS À18%) for CFSR, especially in the dry season.…”

Section: Effect Of Different Meteorological Datasets As Inputcontrasting

confidence: 69%

Application of meteorological element combination-driven SWAT model based on meteorological datasets in alpine basin

Liu

et al. 2021

Water Supply

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Thus far, reanalysis-based meteorological products have drawn little attention to the influence of meteorological elements of products on hydrological modeling. This study aims to evaluate the hydrological application potential of the precipitation, temperature, and solar radiation of the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR) in an alpine basin. The precipitation, temperature, and solar radiation of the gauge-observed meteorological dataset (GD), CFSR, and CMADS were cross-combined, and 20 scenarios were constructed to drive the SWAT model. From the comprehensive comparisons of all scenarios, we drew the following conclusions: (1) among the three meteorological elements, precipitation has the greatest impact on the simulation results, and using GD precipitation from sparse stations yielded better performance than CMADS and CFSR; (2) although the SWAT modeling driven by CMADS and CFSR performed poorly, with CMADS underestimation and CFSR overestimation, the temperature and solar radiation of CMADS and CFSR can be an alternative data source for streamflow simulation; (3) models using GD precipitation, CFSR temperature, and CFSR solar radiation as input yielded the best performance in streamflow simulation, suggesting that these data sources can be applied to this data-scarce alpine region.

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“…When establishing the hydrological model, the spatial resolution of the simulation dataset was high, and available CMADS data were thus employed. Compared with the Climatic Research Unit (CRU) data and other widely used datasets, CMADS data have a higher spatial resolution and are more suitably applied in a small watershed [43][44][45][46][47]. For a watershed lacking meteorological data, the CMADS dataset can ensure accuracy on large spatial and temporal scales.…”

Section: Discussionmentioning

confidence: 99%

Hydrological process simulation in Manas River Basin using CMADS

Yang

et al. 2020

Open Geosciences

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The inability to conduct hydrological simulations in areas that lack historical meteorological data is an important factor limiting the development of watershed models, understanding of watershed water resources, and ultimate development of effective sustainability policies. This study focuses on the Manas River Basin (MRB), which is a high-altitude area with no meteorological stations and is located on the northern slope of the Tianshan Mountains, northern China. The hydrological processes were simulated using the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) using the Soil and Water Assessment Tool (SWAT) model. Simulated runoff was corrected using calibration/uncertainty and sensitivity program for the SWAT. Through parameter sensitivity analysis, parameter calibration, and verification, the Nash–Sutcliffe efficiency (NSE), adjusted R-square ({R}_{\text{adj}}^{2}), and percentage bias (\text{PBIAS}) were selected for evaluation. The results were compared with statistics obtained from Kenswat Hydrological Station, where the monthly runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.64, {R}_{\text{adj}}^{2}\hspace{.25em}=0.69, and \text{PBIAS}\hspace{.25em}=\mbox{--}0.9, and the daily runoff simulation efficiency was \text{NSE}\hspace{.25em}=0.75, {R}_{\text{adj}}^{2} = 0.75, \text{PBIAS} = −1.5. These results indicate that by employing CMADS data, hydrological processes within the MRB can be adequately simulated. This finding is significant, as CMADS provide continuous temporal, detailed, and high-spatial-resolution meteorological data that can be used to build a hydrological model with adequate accuracy in areas that lack historical meteorological data.

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Evaluation of Hydrological Application of CMADS in Jinhua River Basin, China

Cited by 10 publications

References 49 publications

Application of Meteorological Element Combination-Driven SWAT Model based on Meteorological Datasets in Alpine catchment: A case study in the Yellow River Source Region (China)

Application of Meteorological Element Combination-Driven SWAT Model based on Meteorological Datasets in Alpine catchment: A case study in the Yellow River Source Region (China)

Application of meteorological element combination-driven SWAT model based on meteorological datasets in alpine basin

Hydrological process simulation in Manas River Basin using CMADS

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