Arid
DOI10.1080/15481603.2021.1947622
Estimating evapotranspiration based on the satellite-retrieved near-infrared reflectance of vegetation (NIRv) over croplands
Tang, Lili; Zhang, Sha; Zhang, Jiahua; Liu, Yan; Bai, Yun
通讯作者Bai, Y (corresponding author), Qingdao Univ, Coll Comp Sci & Technol, Res Ctr Remote Sensing Informat & Digital Earth, Qingdao, Peoples R China.
来源期刊GISCIENCE & REMOTE SENSING
ISSN1548-1603
EISSN1943-7226
出版年2021
卷号58期号:6页码:889-913
英文摘要Accurate information on cropland evapotranspiration (ET) can facilitate effective agricultural management. However, the application of existing physical models over broad regions may be impeded due to the need for difficult to acquire information about environmental factors that constrain ET. The recently developed near-infrared reflectance of vegetation (NIRv), which can reasonably characterize ecosystem photosynthesis without the need for additional environmental information, is potentially useful for estimating cropland ET and reducing the difficulty in ET modeling. As such, we proposed two simply formulated semi-empirical models that utilize NIRv as a major factor constraining cropland ET. The first model, termed Penman-Monteith+ (PM+), computed canopy transpiration using the PM equation along with canopy conductance values estimated from NIRv-derived gross primary productivity (NIRv-GPP) and calculated soil evaporation using an empirical approach. Another model, termed underlying water-use efficiency+ (uWUE+), used the uWUE approach along with the NIRv-GPP to predict ET. We calibrated and validated PM+ and uWUE+ over 32 cropland flux sites and then compared them with six complex models. The better model between PM+ and uWUE+ was applied to estimate regional ET over North China Plain (NCP), where typical C-3 and C-4 crops were planted during 2010-2018, along with remote sensing and meteorological data. Results indicated that the two new models can reasonably estimate cropland ET. The PM+ model reproduced an eight-day value of ET (denoted as eight-day ET) with R-2 = 0.741 and RMSE = 5.638 mm/8d, slightly better than the uWUE+ model (R-2 = 0. 674 and RMSE = 6.275 mm/8d) for a cross-site validation over 17 flux sites of the validation dataset. Site-level validation revealed consistently better performance of PM+ compared to uWUE+ over most flux sites. For the comparisons with six existing models, PM+ can perform better than all these models and uWUE+ is better than five of them. Subsequently, the PM+ (uWUE+) model reasonably reproduced eight-day ET over four sites under a dry climate (Arid Index <= 0.5) with site-level R-2 = 0.691 (0.617) and RMSE = 6.663 (7.906) mm/8d on average, which is better than the six existing models. In addition, the regional mean annual ET varied from 590 mm per year (mm/yr) to 680 mm/yr over NCP with a significant increasing trend of 9.05 mm/yr (p < 0.01), and the ET values in maize growing season were higher than that in wheat growing season. Our results demonstrated that the simply formulated PM+ and uWUE+ models can provide simple and robust approaches to estimate regional and global cropland ET.
英文关键词NIRv-driven GPP evapotranspiration Penman-Monteith underlying water-use efficiency arid regions
类型Article
语种英语
收录类别SCI-E
WOS记录号WOS:000675733500001
WOS关键词WATER-USE EFFICIENCY ; GROSS PRIMARY PRODUCTIVITY ; NET ECOSYSTEM CARBON ; BALANCE SYSTEM SEBS ; LATENT-HEAT FLUX ; SURFACE-ENERGY ; SOIL-MOISTURE ; CANOPY CONDUCTANCE ; CO2 EXCHANGE ; MODIS
WOS类目Geography, Physical ; Remote Sensing
WOS研究方向Physical Geography ; Remote Sensing
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/363444
作者单位[Tang, Lili; Zhang, Sha; Zhang, Jiahua; Liu, Yan; Bai, Yun] Qingdao Univ, Coll Comp Sci & Technol, Res Ctr Remote Sensing Informat & Digital Earth, Qingdao, Peoples R China; [Zhang, Jiahua] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China
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GB/T 7714
Tang, Lili,Zhang, Sha,Zhang, Jiahua,et al. Estimating evapotranspiration based on the satellite-retrieved near-infrared reflectance of vegetation (NIRv) over croplands[J],2021,58(6):889-913.
APA Tang, Lili,Zhang, Sha,Zhang, Jiahua,Liu, Yan,&Bai, Yun.(2021).Estimating evapotranspiration based on the satellite-retrieved near-infrared reflectance of vegetation (NIRv) over croplands.GISCIENCE & REMOTE SENSING,58(6),889-913.
MLA Tang, Lili,et al."Estimating evapotranspiration based on the satellite-retrieved near-infrared reflectance of vegetation (NIRv) over croplands".GISCIENCE & REMOTE SENSING 58.6(2021):889-913.
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