Applicability of CMADS in Runoff Simulation of Huotong River Basin Based on SWAT Model
The scarcity of meteorological data leads to the limitation of hydrological model research,which also exists in small and medium-sized rive basins along the southeastern coastal areas of China.The China meteorological assimilation dataset (CMADS) is the available meteorological dataset,which aims to...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Pearl River
2021-01-01
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| Series: | Renmin Zhujiang |
| Subjects: | |
| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2021.10.001 |
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| Summary: | The scarcity of meteorological data leads to the limitation of hydrological model research,which also exists in small and medium-sized rive basins along the southeastern coastal areas of China.The China meteorological assimilation dataset (CMADS) is the available meteorological dataset,which aims to filling the gap of data scarcity in hydrological model.Therefore,it is particularly important to verify the applicability of this dataset in runoff simulation based on SWAT model.Taking the Fujian Huotong River basin as the object,and the data of the survey station as the reference,this paper evaluates the applicability of CMADS by using the data consistency evaluation,the test coefficient of runoff simulation based on SWAT model and the spatial distribution of hydrological elements.The results show that:The spatial distribution of precipitation in the two types of data is consistent,and the correlation of temperature data is high.The R<sup>2</sup> and NSE coefficients of the monthly and daily runoff simulation results based on SWAT model obtained from the CMADS and the survey stations are satisfactory.The hydrological components of the CMADS model have little deviation from that of the survey station with consistent spatial distribution.Therefore,it can be concluded that the CMADS has good applicability in the runoff simulation of representative river basins along the southeast coastal area of China. |
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| ISSN: | 1001-9235 |