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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #381793

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Applications of a thermal-based two-source energy balance model coupling the sun-induced chlorophyll fluorescence data

Author
item SONG, L. - Chongqing University
item DING, Z. - Chongqing University
item Kustas, William - Bill
item HUA, W. - Imperial College
item LIU, X. - Chinese Academy Of Sciences
item LIU, L. - Chinese Academy Of Sciences
item LIU, S. - Chinese Academy Of Sciences
item MA, M. - Southwest University
item BAI, Y. - Collaborator
item XU, Z. - Beijing Normal University

Submitted to: IEEE Geoscience and Remote Sensing Magazine
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/19/2023
Publication Date: 2/10/2023
Citation: Song, L., Ding, Z., Kustas, W.P., Hua, W., Liu, X., Liu, L., Liu, S., Ma, M., Bai, Y., Xu, Z. 2023. Applications of a thermal-based two-source energy balance model coupling the sun-induced chlorophyll fluorescence data . IEEE Geoscience and Remote Sensing Magazine. 20:2500705. https://doi.org/10.1109/LGRS.2023.3240996.
DOI: https://doi.org/10.1109/LGRS.2023.3240996

Interpretive Summary: The two-source energy balance (TSEB) model using remotely sensed land surface temperature from satellites as a key boundary condition for estimating crop water use or evapotranspiration (ET) has been shown to improve agricultural water management and conservation. However, the TSEB model does not always properly partition ET into plant transpiration and soil evaporation components when using the original formulation for canopy transpiration. Earth observations from new satellite sensors detecting plant canopy photosynthesis from suninduced chlorophyll fluorescence (SIF) data have the potential to improve the transpiration algorithm in TSEB. In this pilot study, SIF data available from a tower-based sensor are coupled to the TSEB model by developing a mechanistic SIF-transpiration relationship (TSEB-SIF). While the TSEB-SIF model yields only slight improvement in ET estimation compared to the original TSEB formulation, TSEB-SIF produces more accurate partitioning of ET into plant transpiration and soil evaporation. More reliable estimation of transpiration will result in improved monitoring of crop water stress and in the estimation of crop water use efficiency resulting in enhanced agricultural water management and conservation.

Technical Abstract: Quantifying and monitoring land surface evapotranspiration (ET) is an essential task for understanding the earth water, energy and carbon cycles. ET, specifically plant transpiration (T) is closely linked to the photosynthesis which is coupled through stomatal function. However, the mechanistic links between Sun-induced chlorophyll fluorescence (SIF) information indicating canopy photosynthetic activity, and T are complex and difficult to be derived empirically. A mechanistic SIF-T relationship at ecosystem scale was developed and coupled to the two source energy balance model (TSEB-SIF) to estimate the ET and its components, T and soil evaporation, E. By comparing model predictions with observations from an irrigated cropland site located in a semiarid region, the TSEB-SIF model shows a slightly better performance to the TSEB model in estimating ET, especially under water deficit conditions. Moreover, the TSEB-SIF model more reliably partitioned the T from ET while the TSEB model tended to overestimate the ratio of T/ET.