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

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. Physically-based 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 (G_c) 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 G_c. 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 G_c, 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 regional estimates using remote sensing SIF satellites such as from TROPOspheric Monitoring Instrument (TROPOMI), Orbiting Carbon Observatory-3 (OCO-3), or with the upcoming FLuorescence EXplorer (FLEX) mission, among others.