Modeling transpiration using solar-induced chlorophyll fluorescence and photochemical reflectance index synergistically in a closed-canopy winter wheat ecosystem
文献类型：期刊论文
| 作者 | Zheng, Chen1,2,3,4; Wang, Shaoqiang1,2,5; Chen, Jing M.3,4; Xiao, Jingfeng6; Chen, Jinghua1,2; Zhu, Kai1,2; Sun, Leigang7,8 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2024-03-01 |
| 卷号 | 302页码:20 |
| ISSN号 | 0034-4257 |
| 关键词 | Transpiration Photochemical reflectance index Sun-induced chlorophyll fluorescence Non-photochemical quenching Hybrid model SCOPE model |
| DOI | 10.1016/j.rse.2023.113981 |
| 通讯作者 | Wang, Shaoqiang(sqwang@igsnrr.ac.cn) |
| 英文摘要 | The joint use of solar-induced chlorophyll fluorescence (SIF) and the photochemical reflectance index (PRI) has been shown to improve gross primary productivity (GPP) estimation across various plant functional types. However, the utility of PRI in combination with SIF for transpiration (T) estimation has not yet been explored. Additionally, current SIF-driven transpiration models including linear models, semi-mechanical models (combination of canopy conductance, gc, derived from a SIF and vapor pressure deficit, VPD, driven linear model with the Penman-Monteith model), and hybrid models (combination of gc derived from a SIF and VPD driven machine learning model with the Penman-Monteith model) have rarely been mutually assessed. Based on concurrent remotely sensed SIF and PRI, and eddy covariance flux measurements during one growing season for a winter wheat ecosystem in northern China, we investigated the mediating effect of PRI on SIF-driven T estimation under different VPD conditions and compared the performance of linear, semi-mechanical, and hybrid models in estimating T. Our results showed that the mediating effect of PRI on T described in the SIF-driven linear, semi-mechanistic, and hybrid models was significant under high VPD conditions rather than under low VPD conditions. Specifically, based on T partitioned using an underlying water use efficiency method as a benchmark, the root mean square error (RMSE) value of the PRI-mediated linear, semi-mechanistic, and hybrid models was 28.01 W/m(2), 22.25 W/m(2), and 28.71 W/m(2) lower, respectively, than those of the corresponding models without PRI when VPD was >1.5 kPa. Based on T partitioned using a transpiration estimation algorithm as a benchmark, these three models also exhibited a significant reduction in RMSE under high VPD conditions after considering PRI. The main rationale behind the PRI improvement is that PRI can track photosynthetic dynamics under high VPD conditions. Based on the simulation results of the Soil-Canopy-Observation of Photosynthesis and Energy fluxes (SCOPE) model, PRI can serve as an indicator for non-photochemical quenching (NPQ) within this ecosystem. Consequently, PRI can enhance the capability of SIF to characterize the energy dissipation of photosynthetically active radiation and help SIF to yield more accurate information on GPP and gc under high VPD conditions. Finally, the order of model performance in estimating T was generally hybrid model > semi-mechanistic model > linear model. Our findings show the effectiveness of PRI for improving SIF-driven transpiration estimation under high VPD conditions and provide a new hybrid model for estimating T from SIF. |
| WOS关键词 | LIGHT USE EFFICIENCY ; TEMPERATE DECIDUOUS FOREST ; RADIATION USE EFFICIENCY ; WATER-STRESS DETECTION ; STOMATAL CONDUCTANCE ; OPTICAL INDICATOR ; AIRBORNE IMAGERY ; SAP FLOW ; PRI ; PHOTOSYNTHESIS |
| 资助项目 | National Natural Science Foundation of China[42250205] ; National Natural Science Foundation of China[42101479] ; China Postdoctoral Science Foundation[2020 M680654] |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | ELSEVIER SCIENCE INC |
| WOS记录号 | WOS:001156778600001 |
| 资助机构 | National Natural Science Foundation of China ; China Postdoctoral Science Foundation |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/202614]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Shaoqiang |
| 作者单位 | 1.Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 3.Univ Toronto, Dept Geog, Toronto, ON M5S 3G3, Canada 4.Univ Toronto, Program Planning, Toronto, ON M5S 3G3, Canada 5.Chinese Univ Geosci, Sch Geog & Informat Engn, Key Lab Reg Ecol Proc & Environm Evolut, Wuhan 430074, Peoples R China 6.Univ New Hampshire, Inst Study Earth Oceans & Space, Earth Syst Res Ctr, Durham, NH 03824 USA 7.Inst Geog Sci, Hebei Acad Sci, Shijiazhuang 050011, Peoples R China 8.Hebei Technol Innovat Ctr Geog Informat Applicat, Shijiazhuang 050011, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zheng, Chen,Wang, Shaoqiang,Chen, Jing M.,et al. Modeling transpiration using solar-induced chlorophyll fluorescence and photochemical reflectance index synergistically in a closed-canopy winter wheat ecosystem[J]. REMOTE SENSING OF ENVIRONMENT,2024,302:20. |
| APA | Zheng, Chen.,Wang, Shaoqiang.,Chen, Jing M..,Xiao, Jingfeng.,Chen, Jinghua.,...&Sun, Leigang.(2024).Modeling transpiration using solar-induced chlorophyll fluorescence and photochemical reflectance index synergistically in a closed-canopy winter wheat ecosystem.REMOTE SENSING OF ENVIRONMENT,302,20. |
| MLA | Zheng, Chen,et al."Modeling transpiration using solar-induced chlorophyll fluorescence and photochemical reflectance index synergistically in a closed-canopy winter wheat ecosystem".REMOTE SENSING OF ENVIRONMENT 302(2024):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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