Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data
Although soil moisture (<i>SM</i>) is an important constraint factor of evapotranspiration (<i>ET</i>), the majority of the satellite-driven <i>ET</i> models do not include <i>SM</i> observations, especially the <i>SM</i> at different depth...
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MDPI AG
2021-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/16/3118 |
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| author | Wanqiu Xing Weiguang Wang Quanxi Shao Linye Song Mingzhu Cao |
| author_facet | Wanqiu Xing Weiguang Wang Quanxi Shao Linye Song Mingzhu Cao |
| author_sort | Wanqiu Xing |
| collection | DOAJ |
| description | Although soil moisture (<i>SM</i>) is an important constraint factor of evapotranspiration (<i>ET</i>), the majority of the satellite-driven <i>ET</i> models do not include <i>SM</i> observations, especially the <i>SM</i> at different depths, since its spatial and temporal distribution is difficult to obtain. Based on monthly three-layer <i>SM</i> data at a 0.25° spatial resolution determined from multi-sources, we updated the original Priestley Taylor–Jet Propulsion Laboratory (PT-JPL) algorithm to the Priestley Taylor–Soil Moisture Evapotranspiration (PT-SM <i>ET</i>) algorithm by incorporating <i>SM</i> control into soil evaporation (<i>E</i><sub>s</sub>) and canopy transpiration (<i>T</i>). Both algorithms were evaluated using 17 eddy covariance towers across different biomes of China. The PT-SM <i>ET</i> model shows increased <i>R</i><sup>2</sup>, <i>NSE</i> and reduced <i>RMSE</i>, Bias, with more improvements occurring in water-limited regions. <i>SM</i> incorporation into <i>T</i> enhanced <i>ET</i> estimates by increasing <i>R</i><sup>2</sup> and <i>NSE</i> by 4% and 18%, respectively, and <i>RMSE</i> and Bias were respectively reduced by 34% and 7 mm. Moreover, we applied the two <i>ET</i> algorithms to the whole of China and found larger increases in <i>T</i> and <i>E</i><sub>s</sub> in the central, northeastern, and southern regions of China when using the PT-SM algorithm compared with the original algorithm. Additionally, the estimated mean annual <i>ET</i> increased from the northwest to the southeast. The <i>SM</i> constraint resulted in higher transpiration estimate and lower evaporation estimate. <i>E</i><sub>s</sub> was greatest in the northwest arid region, interception was a large fraction in some rainforests, and <i>T</i> was dominant in most other regions. Further improvements in the estimation of <i>ET</i> components at high spatial and temporal resolution are likely to lead to a better understanding of the water movement through the soil–plant–atmosphere continuum. |
| first_indexed | 2024-03-10T08:25:39Z |
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| id | doaj.art-b259d638d7aa42fa91f89080c837c935 |
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| language | English |
| last_indexed | 2024-03-10T08:25:39Z |
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| spelling | doaj.art-b259d638d7aa42fa91f89080c837c9352023-11-22T09:32:10ZengMDPI AGRemote Sensing2072-42922021-08-011316311810.3390/rs13163118Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture DataWanqiu Xing0Weiguang Wang1Quanxi Shao2Linye Song3Mingzhu Cao4State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaCSIRO Data 61, Australian Resources Research Centre, Kensington, WA 6151, AustraliaInstitute of Urban Meteorology, China Meteorological Administration, Beijing 100089, ChinaState Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, ChinaAlthough soil moisture (<i>SM</i>) is an important constraint factor of evapotranspiration (<i>ET</i>), the majority of the satellite-driven <i>ET</i> models do not include <i>SM</i> observations, especially the <i>SM</i> at different depths, since its spatial and temporal distribution is difficult to obtain. Based on monthly three-layer <i>SM</i> data at a 0.25° spatial resolution determined from multi-sources, we updated the original Priestley Taylor–Jet Propulsion Laboratory (PT-JPL) algorithm to the Priestley Taylor–Soil Moisture Evapotranspiration (PT-SM <i>ET</i>) algorithm by incorporating <i>SM</i> control into soil evaporation (<i>E</i><sub>s</sub>) and canopy transpiration (<i>T</i>). Both algorithms were evaluated using 17 eddy covariance towers across different biomes of China. The PT-SM <i>ET</i> model shows increased <i>R</i><sup>2</sup>, <i>NSE</i> and reduced <i>RMSE</i>, Bias, with more improvements occurring in water-limited regions. <i>SM</i> incorporation into <i>T</i> enhanced <i>ET</i> estimates by increasing <i>R</i><sup>2</sup> and <i>NSE</i> by 4% and 18%, respectively, and <i>RMSE</i> and Bias were respectively reduced by 34% and 7 mm. Moreover, we applied the two <i>ET</i> algorithms to the whole of China and found larger increases in <i>T</i> and <i>E</i><sub>s</sub> in the central, northeastern, and southern regions of China when using the PT-SM algorithm compared with the original algorithm. Additionally, the estimated mean annual <i>ET</i> increased from the northwest to the southeast. The <i>SM</i> constraint resulted in higher transpiration estimate and lower evaporation estimate. <i>E</i><sub>s</sub> was greatest in the northwest arid region, interception was a large fraction in some rainforests, and <i>T</i> was dominant in most other regions. Further improvements in the estimation of <i>ET</i> components at high spatial and temporal resolution are likely to lead to a better understanding of the water movement through the soil–plant–atmosphere continuum.https://www.mdpi.com/2072-4292/13/16/3118evapotranspirationPriestley–Taylor algorithmsoil moistureevaporationtranspirationChina |
| spellingShingle | Wanqiu Xing Weiguang Wang Quanxi Shao Linye Song Mingzhu Cao Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data Remote Sensing evapotranspiration Priestley–Taylor algorithm soil moisture evaporation transpiration China |
| title | Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data |
| title_full | Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data |
| title_fullStr | Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data |
| title_full_unstemmed | Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data |
| title_short | Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data |
| title_sort | estimation of evapotranspiration and its components across china based on a modified priestley taylor algorithm using monthly multi layer soil moisture data |
| topic | evapotranspiration Priestley–Taylor algorithm soil moisture evaporation transpiration China |
| url | https://www.mdpi.com/2072-4292/13/16/3118 |
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