How does gross primary production uncertainty impact evapotranspiration prediction within the carbon-water coupled model?
文献类型：期刊论文
| 作者 | Huang, Lingxiao1,2; Wang, Yizhe1,2; Liu, Meng3,4; Sun, Yifei1,2; Fan, Rong1,2; Li, Zhao-Liang3,4 |
| 刊名 | JOURNAL OF HYDROLOGY
 |
| 出版日期 | 2026-05-01 |
| 卷号 | 670页码:135131 |
| 关键词 | Evapotranspiration Gross primary production Carbon-water coupled model Remote sensing |
| ISSN号 | 0022-1694 |
| DOI | 10.1016/j.jhydrol.2026.135131 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Carbon-water coupled models, which account for the intrinsic link between terrestrial carbon and water cycles, have been widely applied to simulate evapotranspiration (ET, the second largest flux in the terrestrial water cycle). However, gross primary production (GPP, the largest flux in the terrestrial carbon cycle), a key input variable in carbon-water coupled models, remains highly uncertain in current remote sensing (RS)-based estimations. The extent to which these GPP uncertainties affect ET predictions within coupled modeling frameworks remains poorly understood. In this study, we employed a classical carbon-water coupled modeling framework driven by 11 state-of-the-art RS-based GPP products with varying biases and 20,943 8-day GPP observations to quantitatively assess the impact of GPP uncertainty on ET estimation accuracy. In addition, we used five representative GPP products to drive the coupled model and generated global ET estimates from 2001 to 2015, aiming to investigate how GPP uncertainty shapes the spatiotemporal patterns of ET simulations. Our results demonstrate that GPP uncertainty significantly affected both the accuracy and spatiotemporal patterns of ET estimation. Using the 8-day ET simulations driven by observed GPP as a benchmark, the 11 GPP products with varying degrees of biases on average increased the root mean square error (RMSE) by 26.94% (16.50%-33.25%) and decreased the coefficient of determination (R 2 ) by 13.58% (8.43%-18.07%). Moreover, different GPP inputs led to annual ET differences of up to +/- 200 mm year-1 in some regions and produced highly divergent, and sometimes even opposing, interannual ET trends at global and regional scales from 2001 to 2015. This study highlights that improving GPP accuracy should be prioritized to enhance the reliability of carbon-water coupled modeling, particularly for large-scale hydrological and Earth system applications. |
| URL标识 | 查看原文 |
| WOS关键词 | EDDY COVARIANCE ; GLOBAL DATASETS ; LEAF ; FLUXES ; CONDUCTANCE ; SUNLIT |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:001704237600003 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221373]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Liu, Meng |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; 2.Univ Chinese Acad Sci, Beijing 100101, Peoples R China; 3.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arable Land China, Beijing 100081, Peoples R China; 4.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agr Remote Sensing, Minist Agr & Rural Affairs, Beijing 100081, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Lingxiao,Wang, Yizhe,Liu, Meng,et al. How does gross primary production uncertainty impact evapotranspiration prediction within the carbon-water coupled model?[J]. JOURNAL OF HYDROLOGY,2026,670:135131. |
| APA | Huang, Lingxiao,Wang, Yizhe,Liu, Meng,Sun, Yifei,Fan, Rong,&Li, Zhao-Liang.(2026).How does gross primary production uncertainty impact evapotranspiration prediction within the carbon-water coupled model?.JOURNAL OF HYDROLOGY,670,135131. |
| MLA | Huang, Lingxiao,et al."How does gross primary production uncertainty impact evapotranspiration prediction within the carbon-water coupled model?".JOURNAL OF HYDROLOGY 670(2026):135131. |
入库方式： OAI收割
来源：地理科学与资源研究所
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