Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China
Reanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/12/4/996 |
| _version_ | 1797571834635354112 |
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| author | Limin Zhang Xianyong Meng Hao Wang Mingxiang Yang Siyu Cai |
| author_facet | Limin Zhang Xianyong Meng Hao Wang Mingxiang Yang Siyu Cai |
| author_sort | Limin Zhang |
| collection | DOAJ |
| description | Reanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR), against gauge observations (OBS) by using interpolation software and statistical indicators in Northeast China (NEC), as well as their annual average spatial and monthly average distributions. The reliability and applicability of the two reanalysis datasets were assessed as inputs in a hydrological model (SWAT) for runoff simulation in the Hunhe River Basin. Statistical results reveal that CMADS performed better than CFSR for precipitation and temperature in NEC with the indicators closer to optimal values (the ratio of standard deviations of precipitation and maximum/minimum temperature from CMADS were 0.92, 1.01, and 0.995, respectively, while that from CFSR were 0.79, 1.07, and 0.897, respectively). Hydrological modelling results showed that CMADS + SWAT and OBS + SWAT performed far better than CFSR + SWAT on runoff simulations. The Nash‒Sutcliffe efficiency (NSE) of CMADS + SWAT and OBS + SWAT ranged from 0.54 to 0.95, while that of CFSR + SWAT ranged from −0.07 to 0.85, exhibiting poor performance. The CMADS reanalysis dataset is more accurate than CFSR in NEC and is a suitable input for hydrological simulations. |
| first_indexed | 2024-03-10T20:46:17Z |
| format | Article |
| id | doaj.art-c5e3f63b0bc548cca7fb6b58232dcfe0 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-10T20:46:17Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-c5e3f63b0bc548cca7fb6b58232dcfe02023-11-19T20:19:57ZengMDPI AGWater2073-44412020-04-0112499610.3390/w12040996Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast ChinaLimin Zhang0Xianyong Meng1Hao Wang2Mingxiang Yang3Siyu Cai4College of Architecture and Civil Engineering, Beijing University of Technology (BJUT), Beijing 100124, ChinaCollege of Resources and Environmental Science, China Agricultural University (CAU), Beijing 100094, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin&China Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin&China Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaState Key Laboratory of Simulation and Regulation of Water Cycle in River Basin&China Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaReanalysis datasets can provide alternative and complementary meteorological data sources for hydrological studies or other scientific studies in regions with few gauge stations. This study evaluated the accuracy of two reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and Climate Forecast System Reanalysis (CFSR), against gauge observations (OBS) by using interpolation software and statistical indicators in Northeast China (NEC), as well as their annual average spatial and monthly average distributions. The reliability and applicability of the two reanalysis datasets were assessed as inputs in a hydrological model (SWAT) for runoff simulation in the Hunhe River Basin. Statistical results reveal that CMADS performed better than CFSR for precipitation and temperature in NEC with the indicators closer to optimal values (the ratio of standard deviations of precipitation and maximum/minimum temperature from CMADS were 0.92, 1.01, and 0.995, respectively, while that from CFSR were 0.79, 1.07, and 0.897, respectively). Hydrological modelling results showed that CMADS + SWAT and OBS + SWAT performed far better than CFSR + SWAT on runoff simulations. The Nash‒Sutcliffe efficiency (NSE) of CMADS + SWAT and OBS + SWAT ranged from 0.54 to 0.95, while that of CFSR + SWAT ranged from −0.07 to 0.85, exhibiting poor performance. The CMADS reanalysis dataset is more accurate than CFSR in NEC and is a suitable input for hydrological simulations.https://www.mdpi.com/2073-4441/12/4/996CMADSCFSRreanalysis dataNortheast ChinaSWAT |
| spellingShingle | Limin Zhang Xianyong Meng Hao Wang Mingxiang Yang Siyu Cai Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China Water CMADS CFSR reanalysis data Northeast China SWAT |
| title | Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China |
| title_full | Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China |
| title_fullStr | Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China |
| title_full_unstemmed | Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China |
| title_short | Investigate the Applicability of CMADS and CFSR Reanalysis in Northeast China |
| title_sort | investigate the applicability of cmads and cfsr reanalysis in northeast china |
| topic | CMADS CFSR reanalysis data Northeast China SWAT |
| url | https://www.mdpi.com/2073-4441/12/4/996 |
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