Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China
The land surface model (LSM) is extensively utilized to simulate terrestrial processes between land surface and atmosphere in the Earth system. Hydrology simulation is the key component of the model, which can directly reflect the capability of LSM. In this study, three offline LSM simulations were...
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MDPI AG
2024-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/3/550 |
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| author | Dayang Wang Dagang Wang Yiwen Mei Qing Yang Mingfei Ji Yuying Li Shaobo Liu Bailian Li Ya Huang Chongxun Mo |
| author_facet | Dayang Wang Dagang Wang Yiwen Mei Qing Yang Mingfei Ji Yuying Li Shaobo Liu Bailian Li Ya Huang Chongxun Mo |
| author_sort | Dayang Wang |
| collection | DOAJ |
| description | The land surface model (LSM) is extensively utilized to simulate terrestrial processes between land surface and atmosphere in the Earth system. Hydrology simulation is the key component of the model, which can directly reflect the capability of LSM. In this study, three offline LSM simulations were conducted over China using the Community Land Model version 5.0 (CLM5) driven by different meteorological forcing datasets, namely China Meteorological Forcing Dataset (CMFD), Global Soil Wetness Project Phase 3 (GSWP3), and bias-adjusted ERA5 reanalysis (WFDE5), respectively. Both gridded and in situ reference data, including evapotranspiration (ET), soil moisture (SM), and runoff, were employed to evaluate the performance levels of three CLM5-based simulations across China and its ten basins. In general, all simulations realistically replicate the magnitudes, spatial patterns, and seasonal cycles of ET over China when compared with remote-sensing-based ET observations. Among ten basins, Yellow River Basin (YRB) is the basin where simulations are the best, supported by the higher KGE value of 0.79. However, substantial biases occur in Northwest Rivers Basin (NWRB) with significant overestimation for CMFD and WFDE5 and underestimation for GSWP3. In addition, both grid-based or site-based evaluations of SM indicate that systematic wet biases exist in all three CLM5 simulations for shallower soil layer over nine basins of China. Comparatively, the performance levels in simulating SM for deeper soil layer are slightly better. Moreover, all three types of CLM5 simulate reasonable runoff spatial patterns, among which CMFD can capture more detailed information, but GSWP3 presents more comparable change trends of runoff when compared to the reference data. In summary, this study explored the capacity of CLM5 driven by different meteorological forcing data, and the assessment results may provide important insights for the future developments and applications of LSM. |
| first_indexed | 2024-03-08T03:50:10Z |
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| id | doaj.art-c5937d9a77da41b78b52932c881e3be2 |
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| language | English |
| last_indexed | 2024-03-08T03:50:10Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj.art-c5937d9a77da41b78b52932c881e3be22024-02-09T15:21:27ZengMDPI AGRemote Sensing2072-42922024-01-0116355010.3390/rs16030550Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over ChinaDayang Wang0Dagang Wang1Yiwen Mei2Qing Yang3Mingfei Ji4Yuying Li5Shaobo Liu6Bailian Li7Ya Huang8Chongxun Mo9Overseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, School of Water Resource and Environmental Engineering, Nanyang Normal University, Nanyang 473061, ChinaSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, ChinaSchool of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, ChinaSchool of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USAOverseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, School of Water Resource and Environmental Engineering, Nanyang Normal University, Nanyang 473061, ChinaOverseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, School of Water Resource and Environmental Engineering, Nanyang Normal University, Nanyang 473061, ChinaOverseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, School of Water Resource and Environmental Engineering, Nanyang Normal University, Nanyang 473061, ChinaInternational Center for Ecology and Sustainability, University of California, Riverside, CA 93106, USAState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 211098, ChinaCollege of Civil Engineering and Architecture, Guangxi University, Nanning 530004, ChinaThe land surface model (LSM) is extensively utilized to simulate terrestrial processes between land surface and atmosphere in the Earth system. Hydrology simulation is the key component of the model, which can directly reflect the capability of LSM. In this study, three offline LSM simulations were conducted over China using the Community Land Model version 5.0 (CLM5) driven by different meteorological forcing datasets, namely China Meteorological Forcing Dataset (CMFD), Global Soil Wetness Project Phase 3 (GSWP3), and bias-adjusted ERA5 reanalysis (WFDE5), respectively. Both gridded and in situ reference data, including evapotranspiration (ET), soil moisture (SM), and runoff, were employed to evaluate the performance levels of three CLM5-based simulations across China and its ten basins. In general, all simulations realistically replicate the magnitudes, spatial patterns, and seasonal cycles of ET over China when compared with remote-sensing-based ET observations. Among ten basins, Yellow River Basin (YRB) is the basin where simulations are the best, supported by the higher KGE value of 0.79. However, substantial biases occur in Northwest Rivers Basin (NWRB) with significant overestimation for CMFD and WFDE5 and underestimation for GSWP3. In addition, both grid-based or site-based evaluations of SM indicate that systematic wet biases exist in all three CLM5 simulations for shallower soil layer over nine basins of China. Comparatively, the performance levels in simulating SM for deeper soil layer are slightly better. Moreover, all three types of CLM5 simulate reasonable runoff spatial patterns, among which CMFD can capture more detailed information, but GSWP3 presents more comparable change trends of runoff when compared to the reference data. In summary, this study explored the capacity of CLM5 driven by different meteorological forcing data, and the assessment results may provide important insights for the future developments and applications of LSM.https://www.mdpi.com/2072-4292/16/3/550community land modelmeteorological forcingevapotranspirationsoil moisturerunoffChina |
| spellingShingle | Dayang Wang Dagang Wang Yiwen Mei Qing Yang Mingfei Ji Yuying Li Shaobo Liu Bailian Li Ya Huang Chongxun Mo Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China Remote Sensing community land model meteorological forcing evapotranspiration soil moisture runoff China |
| title | Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China |
| title_full | Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China |
| title_fullStr | Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China |
| title_full_unstemmed | Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China |
| title_short | Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China |
| title_sort | estimates of the land surface hydrology from the community land model version 5 clm5 with three meteorological forcing datasets over china |
| topic | community land model meteorological forcing evapotranspiration soil moisture runoff China |
| url | https://www.mdpi.com/2072-4292/16/3/550 |
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