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This research was jointly funded by the Key Project of the National Natural Science Foundation of China (No. 42330506), the General Program of the National Science Foundation of China (No. 42071054), the EU and Innovation Fund Denmark (IFD) for funding the FORWARD collaborative international consortium (ERA-NET co-fund WaterWorks2015Water JPI initiative); Danida Fellowship Centre (EOForChina project, file number: 18-M01-DTU); Innovation Fund Denmark (ChinaWaterSense project, file number: 8087-00002B) and from the INTEGRATYON3 project (PID2020-117825GB-C21 and C22) through the Spanish Ministry of Economy and Competitiveness and projects BAGAMET (P20_00016) and Adquisicion de Equipamiento cientifico-tecnico (IE17_5560_EEZA), funded by the Counseling of Economy, Innovation, Science and Employment from the Government of Andalucia, all including European Union ERDF funds, and the China Scholarship Council. This work used meteorological and eddy covariance data at CN-Du2, US-Var, US-Wkg, and US-SRM acquired and shared by the FLUXNET (http://fluxnet.fluxdata.org/data/fluxnet2015-dataset/) and AMERIFLUX community (https://ameriflux.lbl.gov/). Gentine acknowledges funding from NASA grant 80NSSC20K1792 P00002 and NNX16AO16H S004. The contiguous solar-induced fluorescence (CSIF) datasets were downloaded from the OSF CSIF repository (https://osf. io/8xqy6/) developed by Yao Zhang and colleagues. MM and TEM acknowledge the support of the Alexander von Humboldt Foundation and the 2013 Max Planck Research Prize to Markus Reichstein for funding the research site ES-LM2. ALB was supported by a Juan de la Cierva-Incorporacion postdoctoral contract IJC2020-045630-I funded by MCIN/AEI /10.13039/501100011033 and by European Union NextGenerationEU/PRTR.

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Dryland evapotranspiration from remote sensing solar-induced chlorophyll fluorescence: Constraining an optimal stomatal model within a two-source energy balance model

Publicated to:Remote Sensing Of Environment. 303 113999- - 2024-01-26 303(), DOI: 10.1016/j.rse.2024.113999

Authors: Bu, Jingyi; Gan, Guojing; Chen, Jiahao; Su, Yanxin; Yuan, Mengjia; Gao, Yanchun; Domingo, Francisco; Lopez-Ballesteros, Ana; Migliavacca, Mirco; El-Madany, Tarek S; Gentine, Pierre; Xiao, Jingfeng; Garcia, Monica

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Abstract

Evapotranspiration (ET) represents the largest water loss flux in drylands, but ET and its partition into plant transpiration (T) and soil evaporation (E) are poorly quantified, especially at fine temporal scales. Physicallybased remote sensing models relying on sensible heat flux estimates, like the two-source energy balance model, could benefit from considering more explicitly the key effect of stomatal regulation on dryland ET. The objective of this study is to assess the potential of satellite-based solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary productivity (GPP), to constrain canopy conductance (Gc) of an optimal stomatal model within a two-source energy balance model in drylands. We assessed our ET model forced with in situ eddy covariance GPP as a benchmark, and compared with GPP estimates based on the Contiguous solar-induced chlorophyll fluorescence (CSIF) remote sensing product, with and without the effect of root-zone soil moisture on the Gc. The estimated ET was robust across four steppes and two tree-grass dryland ecosystems. Comparison of ET simulated using in situ GPP against ET measurements yielded an average coefficient of determination (R2) of 0.74 (0.87) and root-mean-square error (RMSE) of 0.030 (0.35) mm at half-hourly (daily) timescale. For the CSIF model, the average RMSE for ET estimates was 0.036 (0.46) mm. Including explicitly the soil moisture effect on Gc, R2 for ET simulated using CSIF increased from 0.68 (0.82) to 0.77 (0.89), with RMSE ranging between 0.023 (0.21) and 0.040 (0.49) mm depending on the site. The ET partitioning using CSIF is also consistent with model partitioning based on EC GPP using the underlying water use efficiency method. In addition to the site-level model simulations, we conducted a regional application in the Southwest US drylands, with the model calibrated against the remote sensing land surface temperature. Our results demonstrate the capacity of SIF to estimate subdaily and daily ET fluxes in drylands. SIF can provide effective vegetation signals to constrain stomatal conductance and partition ET into T and E similar to those from EC GPP. This approach could be extended for

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